the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Jun 2022
Exploring TikTok as an effective platform for geoscience communication
Abstract. With TikTok emerging as one of the most popular social media platforms, there is significant potential for science communicators to capitalize on this success and share their science with a broad, engaged audience. While videos of chemistry and physics experiments are prominent among educational science content on TikTok, videos related to the geosciences are comparatively lacking, as is an analysis of what types of geoscience videos perform well on TikTok. To increase the visibility of the geosciences and geophysics on TikTok and to determine best strategies for effective geoscience communication on the app, we created a TikTok account called “Terra Explore” (@TerraExplore). The Terra Explore account is a joint effort between science communication specialists at UNAVCO, IRIS, and OpenTopography. We produced 48 educational geoscience videos over a four-month period between October 2021 and February 2022. We evaluated the performance of each video based on its reach, engagement, and viewer retention to determine the qualities of a successful video. Our video topics primarily focused on seismology, earthquakes, topography, lidar (light detection and ranging), and GPS (Global Positioning System), in alignment with our organizational missions. Over this time period, our videos garnered over 2 million total views, and our account gained over 12,000 followers. The videos that received the most views received nearly all (~97 %) of their views from the For You page, TikTok’s algorithmic recommendation feed. We found that short videos (< 20 s) had a high viewer retention rate, but they often had a low engagement rate, leading to less overall visibility. Lecture-style videos that were between 40 seconds and two minutes in length had more success in both reach and engagement. Our videos that went the most viral featured content that was related to a recent newsworthy event (e.g., an earthquake) or explaining place-based geology of a recognizable area. Our results highlight the algorithm-driven nature of TikTok, which results in a low barrier to entry and success for new science communication creators.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Terra Explore. We produced 48 educational geoscience videos and evaluated each video’s performance. Our most-viewed videos received nearly all of their views from TikTok’s algorithmic recommendation feed, and the videos that received the most views were related to a recent newsworthy event (e.g., earthquake) or explained the geology of a recognizable area.
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-494', Anonymous Referee #1, 06 Jul 2022
Note: My familiarity with Tik Tok is minimal and my experience with it is limited to viewing videos that are occasionally forwarded to me. I am, however, familiar with other media platforms and their use for geoscience communication. Furthermore, I am a geoscientist interested in communication and using emerging platforms like TikTok.
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General comments:
The manuscript presents the TikTok analytics data gathered for 48 educational geoscience videos produced and published between Oktober 2021 and February 2022 on the media platform TikTok. Given TikTok’s increase in popularity as a media platform, exploring its potential as a means for geoscience communication is a very merited undertaking. There are no language issues and it’s easy to follow the text. Unfortunately, the study lacks direction and it’s unclear throughout the manuscript what exactly the authors intend to use the TikTok analytics data for. In other words, there’s no apparent experiment design. This is reflected throughout the manuscript in several ways. These include, but are not restricted to, the following:
1) It’s unclear why some of the x-y relationships are looked at (e.g., average view time and total views) and what the implications of a relationship would be. Many figures are redundant or show no patterns, making them seem like simple “data dumps”. (For example, why show gender ratio over time when it does not change?). In other figures, the authors observe patterns I cannot see (e.g., Fig. 3).
2) The last criticism highlights another major flaw of the study, i.e. the complete lack of statistical analyses that would introduce rigor and objectivity in the detection of relationships and patterns in the data. It is difficult to make specific recommendations for methods at this point since I am unsure about the overall goal and experiment design for the study. Given on what I can infer from the presentation and discussion of results, however, I imagine simple correlation analyses and ANOVAs (with “significance” test ) would be suitable for the largest part.
3) The study includes US-centric assumptions that compromise important take-away messages of the study. E.g. the authors use the MST time zone (a US time zone) not just to communicate their results, but also to define the time of the day. This is done without knowledge of the location of the viewers, who may live in a completely different time zone. Since a large portion of topics are or general interest and TikTok is a global media platform, it’s not unreasonable to assume the reach goes beyond the US. If it does, nothing can be said about the preferred viewing time of the audience or, by extension, the optimal time for upload. This could be avoided by good (/more thoughtful) experiment design.
4) The final conclusions and recommendations are mostly not supported by the study due to several of its flaws, the lack of clear (testable) hypotheses and lack of rigorous testing.
As such, I cannot recommend the manuscript for publication. That said, I appreciate the efforts that go into making educational videos and maintaining a presence on a media platform. With the channel and videos, the authors are on good track to test the effectiveness of TikTok (or aspects of it) and I strongly encourage the authors to do so. However, this will require a clearly thought through study/experiment design. This should include a clear idea of what questions should be addressed with the experiment, what hypotheses are tested, what the metrics are used for testing, etc.. This also includes a clear idea of how data (e.g. TikTok analytics data) can be used in it and what its limits are.
Specific comments:
The title is somewhat misleading. The study does not test the effectiveness of TikTok as a platform for geoscience communication. An important part of effective communication is what happens on the receiving side (e.g., information retention). This study looks solely at reach and basic form of engagement.
Line 16 - The term “retention” is a tad misleading. Until it was explained, I took it as a measure for how much of the video was remembered.
Line 20 – What is the “For You” page? If it’s a page with personal video suggestions, maybe use a more general description of it, such as “suggested viewing page (“For You” page on TikTok)” for those unfamiliar with TikTok. It’s explained in section 2, but I’d use a more explanatory and general term for it in the abstract so it doesn’t require knowledge of TikTok.
Line 22 – “Went the most viral” – I’m aware that such terminology has established itself fairly well by now (among specific demographics at least), but I nevertheless recommend rephrasing that for an audience that is unfamiliar with it yet have an interest in exploring such media platforms as a communication tool.
Lines 53-55 – It’s unclear what the purpose and nature of the analysis is. If it is to determine factors of a video that help maximise reach (line 55), why were engagement and view duration analysed at all? Usually, an introduction outlines the broad questions, goals and hypotheses tackles by a study. This helps guide the reader through the manuscript. At this point, I still don’t know what these are or what analyses were conducted on the 3 metrics and for what specific purpose. (Unfortunately, I also miss clarification of this down the line in the following sections).
Lines 58-77 – I appreciate the introduction to TikTok (section 2) and think it’s important. I would add some comments on TikTok’s reach. Who are the viewers, how are they distributed globally? This may be very important information for communicators who want to target specific communities.
Line 67-68 – This is a tad vague. What are these recommendation algorithms based on exactly? The authors list “user’s profile settings”, “location” and “activity”. Can users choose topics of interests in the profile settings? Since the study’s results are, to a degree, sensitive to this, I think a closer look at it and a more elaborate explanation is warranted. This will also help communicators plan their activities on TikTok better.
Line 77 – It’s unclear what is meant by searching sounds. It reads as though sounds are used as hashtags are. Is that accurate?
Lines 85-93: What is the longevity of such hashtags on TikTok? On twitter, for example, they may rapidly change and quickly lose popularity and reach. Is #LearnOnTikTok ongoing and intended as a “stable” hashtag? Was the associated campaign was a one time event or something ongoing and sustainable? If it’s ongoing and the hashtag serves almost like an education “channel” on TikTok now, this should be communicated. As a communicator, this would be very useful for me then. If it’s not expected to survive long as a hashtag, on the other hand, it doesn’t warrant as much explanation.
Lines 104-105: I disagree with the general statement that geoscience does not lend itself to experiment-based content as much. On the contrary, since geoscience is effectively physics and chemistry applied to the Earth, many classic physics and chemistry experiments can be used to demonstrate how something works on Earth. In atmospheric sciences alone, there are plenty of pressure and moisture experiments that can be conducted (at home) to demonstrate important concepts. On the other hand, for Earthquake science, experiments involving concepts of friction and liquefaction come to mind.
Lines 123-124: Was this by design and are there studies of how the metrics used here (reach, engagement and viewing time) vary depending on the gender of the presenter? Given prevailing differences in perception of scientists of different genders, this may be important information for geoscientists who consider TikTok as a communication platform.
Section 4 (general): It’s unclear what determined the choices in video characteristics and how these choices were made with a specific experiment/goal in mind. This is essentially the “experiment setup” section, but I cannot see how the choices made here serve the testing of a broader hypothesis or help answer the study’s overarching question(s). For example, if one were to determine the optimal video length to maximise the engagement rate, one would vary the factor of interest and reduce the number of other free parameters (such as upload time). Reversely, If I wanted to determine the best time to upload a video, I would vary this parameter and keep others constant. I don’t see this type of experiment-based and hypothesis-guided thinking in this section.
Line 175: Please express time using the primary standard UTC (or list in in brackets). As someone who’s not from North America, I was completely unaware of MST.
Fig.2: I think the text-based summary of views is sufficient. The figure does not show any pattern or provides any valuable additional information and thus seems a tad redundant.
Fig 3: Unless most viewers are known to be from North America and ~ the MST time zone, I would change this to UTC. In fact, if the viewer location does not coincide with the MST zone, discussing times of the day may be misleading. Furthermore, I question the merit of presenting this data at all, since (a) there is no clear pattern except maybe an increase in views towards the evening, and (b) global viewers will likely be spread across different time zones.
Fig. 6: The ratio remains ~constant over time, making the figure rather redundant. It’s sufficient to simply state the ratio, as already done in the text.
Lines 215: Please change the term “retention” to something more intuitive like “view duration”. You use the latter term already. I recommend simply sticking to that, also to avoid confusion with viewer information retention (memory).
Fig. 7: It is unclear why video views is plotted against video “view duration”. Is a relationship expected? Why? What would be the meaning of it?
Fig. 8: See comment on Fig. 7. It’s unclear why views are plotted against engagement rate. What would the discovery of a relationship between these metrics help with? What hypothesis or idea would that address?
Fig. 9: See comment on previous 2 figures. What’s would be the significance of the x-y relationship? Furthermore, the caption does not guide the reader through the figure in any way. It does not explain anything and I am left wondering why it is shown and what the authors would like me to see in it.
Section 6.4: I understand why duration and time posted may be valuable information. These may be useful for communicators in their planning to maximise views. However, I do not see the significance of a relationship between views and average % watched.
Section 7: Any thorough, literature-informed discussion of the study’s limitations (and the limits to recommendations made) is missing. For example, I think it would be important to:
- Comment on importance of different metrics for assessing communication effectiveness.
- Comment on how sensitive the study’s results are to the specific algorithms used by TikTok, how transparent they are and how (often) these may change. How does this affect the take-away messages of this study?
- Comment on technology exclusivity and how it limits reach.
- Comment on the effect of video content on audience demographics/nationality/location. This may be important in context of the interpretation of the viewing times also.
Lines 405-412: I question several of these recommendations (and related conclusions) based on some of the study’s flaws:
(a) The recommendation to post earlier in the day seems based on the discussed relationship between time posted and video views. More precisely, it seems based on the observation that videos that received the most views were uploaded in the morning or early afternoon. By simply looking at the data plot, I do not make the same observation. In fact, it is difficult to see any significant pattern at all except maybe a general increase in video views later in the (MST) day. This contradicts the authors’ findings and highlights the need for rigorous statistics to make sure a signal/observation is real. Furthermore, this recommendation is very US centric and/or vague. To elaborate: The authors use a US time zone to define the time of the day. Does the recommendation pertain to MST morning or morning in whatever time zone the communicator lives? To answer this, the authors need to establish where the views are from. If they could establish (1) that their viewers are US (or MST) based, and (2) that there is an actual relationship between views and time of day, a recommendation for upload time could be merited (albeit restricted to the US). As it is, however, no such conclusions can be drawn from the TikTok analytics data.
(b) As a communicator, I want to communicate a specific set of problems and topics. Recommendations to choose a topic based on what is newsworthy (or tied to a specific location) is therefore questionable. This recommendation seems focused on increasing views (regardless of intended subject of communication) rather than on effective communication of a specific topic. The recommendation to include gender-related topics is similarly problematic. I would like to know “What do I do to increase the number of female viewers for videos about this specific topic?” and not “What topic should I choose to increase the number of female viewers.” The recommendation would be merited if the strategy is to include more gender-related topics to gain more female followers, who then view videos of other topics. However, this strategy is also questionable given that relatively few views are gathered from “following” (Fig. 5).
(c) Given how few views the videos got from hashtags (I cannot even see the percentage of it for most of Fig. 5) I do not see how the authors can list this as a recommendation here.
Citation: https://doi.org/10.5194/egusphere-2022-494-RC1 -
AC1: 'Reply on RC1', Emily Zawacki, 27 Jul 2022
We thank the reviewer for their time and helpful comments regarding our manuscript. We believe that with the described additions below to better explain our study, particularly for those that are unfamiliar with TikTok or similar social media analyses, our manuscript will be suitable for publication and of significant value to the science communication community.
Given the total opacity of the TikTok algorithm, our study seeks to elucidate patterns and trends related to reach and engagement of geoscience content on TikTok so that science communicators can find the most success there. More so than any other social media platform, content discovery on TikTok is algorithmically-driven, and our study uses all analytical data metrics available on TikTok to provide insight relevant for science communicators. We specifically analyze (1) reach [video views], (2) video view duration, and (3) video engagement in assessing the impact of each video. We seek to maximize all three factors: (1) videos seen by more people increase the audience impacted by the content, (2) the longer people view a video indicates greater interest in the video and subject, and (3) engaging with the video (like, comment, share) demonstrates additional interest in the video and subject, all reflective of successful science communication.
The videos we created for the Terra Explore TikTok were part of a pilot project to test producing geoscience video content on TikTok. As such, we aimed to produce videos of various topics/styles, durations, with different hashtags used, and different posting times/dates in order to sample parameter space. Although there was not a systematic design to every video, these videos still provide important insight and much needed data for science communication efforts on TikTok. As it is difficult to isolate singular variables, we use the similarity of content and format in GMV (ground motion visualization) videos to more clearly evaluate individual factors. We acknowledge that algorithms may change over time as platforms evolve, but we are not aware of evidence that TikTok is changing its algorithm so rapidly as to invalidate attempts at analysis.
- We survey all available data metrics from TikTok to discern any notable trends in video reach and engagement, as is common with research examining content on social media platforms (see Habibi and Salim, 2021 and Wang et al., 2022 (Geoscience Communication)). We will more specifically describe the purpose of each parameter that we are looking at and what it indicates, as well as our associated hypothesis with how it relates to algorithmic discovery. As an example, social media algorithms are generally believed to reward videos that have a high viewer retention (how long someone watches the video) and high engagement rate by showing the video to more people (as these videos keep users engaged and on the app/platform for longer) (Klug et al., 2021). However, short videos on TikTok (~15s) can very easily yield high viewer retention rates, which doesn’t necessarily translate to high views or engagement. Understanding the data related to each metric is thus important in deciphering what characteristics are likely to make a successful video. Beyond understanding the algorithm itself, a high average view duration and a high engagement rate indicates that the audience is interested and invested in the video content and are extremely useful metrics for evaluating how engaging and successful the video content is.
We will remove the figure depicting gender of followers over time, as a text explanation will suffice.
- We strongly agree that statistical analysis is needed in this study and will greatly strengthen our analyses. We are working on performing correlation analyses for all the relationships we evaluate (including r, r2, and p values to determine statistical significance).
- TikTok provides information about the top territories of an account’s followers and individual video views by region. ~85% of the Terra Explore account’s followers and views are from the United States, which is why we defaulted to a more US-centric view. However, we will include this information related to viewer/follower region and will analyze any videos that have a significant proportion of views from outside the US. We hypothesize that TikTok heavily mines data based on a user’s location and often shows video content local to that viewer. Post time optimization is typically linked to the location where the majority of your audience is, and hence would apply to ‘local morning’ vs ‘local evening.’
- While our videos posted were part of a pilot, we believe that they provide useful information for science communicators, especially given how limited any existing studies of science communication on TikTok are and how untapped the potential of TikTok is.
We will adjust the title of the manuscript so that it more accurately reflects the content.
Line 16: “Viewer retention” (also ‘audience retention’) is a standard metric in social media for the average percentage of a video people watch. However, to keep this term consistent with our figures, we will refer to it as the ‘average video view duration (%)’ throughout.
Line 20: The “For You” page is the Proper Noun name for this feed on TikTok. In the abstract, we define it as “TikTok’s algorithmic recommendation feed.”
Line 22: We will qualify ‘viral’ as high views and engagement.
Lines 53-55: As described in point 1, we will more thoroughly outline our methodology and describe the importance of each metric we analyze. We analyze engagement, as videos with high engagement are hypothesized to be rewarded by the algorithm and will continue to be shown to more people. This cycle of increased engagement and reach thus increases the impact potential of the science content. High engagement rates also indicate an increased interest from the viewer in the video, demonstrating the impact and ‘success’ of the video.
Lines 58-77: We can include additional context regarding the global distribution of TikTok users.
Line 67-68: TikTok provides no information regarding their AI algorithm or how it works, hence why studies like this are important. The information we provide in this section is essentially the extent of all information TikTok publicly makes available. Users can indicate they are ‘not interested’ in a video, but there is no way to choose topics of interest other than watching videos on the app (or skipping them) and liking videos that they enjoy.
Line 77: We recommend downloading TikTok for a brief user experience. Sounds are background audio clips that can be re-used by multiple users and are separate from hashtags.
Lines 85-93: The lifetime of a TikTok hashtag is essentially infinite. You can click on a hashtag and see all videos that have ever been created that use that hashtag. Any person can use any hashtag at any time. As we discuss later in the paper, hashtags on TikTok have a fundamentally different ‘function’ than they do on platforms like Twitter. People generally do not ‘search’ for hashtags on TikTok like they do on Twitter. We hypothesize that hashtags are primarily used in TikTok’s AI to provide additional information and context for the video when deciding who to show it to with the algorithm.
Lines 104-105: We do not say that it is impossible to have experiment videos related to geosciences, merely that they are generally less common and/or easy to produce compared to videos of chemistry and physics experiments. A survey of educational science content on TikTok demonstrates an abundance of videos of chemistry and physics experiments and near total absence of geology-related experiments (which we find is more so related to the ease with which at home or classroom chemistry/physics experiments can be filmed and shared on the app).
Lines 123-124: The video presenters are the existing communications staff at our respective organizations. The male presenter was only able to create two videos during this duration, hence we are unable to analyze video metrics based on the gender of presenter, although this is work we would like to do in the future.
Section 4 (general): As it is very difficult to vary just a singular variable when creating TikTok videos, we use the GMV (ground motion visualization) videos as a way to most clearly isolate variable trends with posting. All the Terra Explore videos were created during a pilot project, in which the goal was to test and produce different types of geoscience content on TikTok (different topics, durations, hashtags used, time and day posted, etc.). Although there was not a systematic design behind every single video posted, that does not make the analyses of these videos any less meaningful.
Line 175: We will include UTC with our time zones.
Fig.2: We will delete this figure.
Fig 3: ~85% of viewers of Terra Explore are within the United States, hence the majority of views come from ‘local’ time zones. The concept of post time upload is related to optimizing the upload of your content for when the majority of users/followers will be active on the app so that it is seen by the highest number of people. All our most highly viewed videos (>90,000 views) were posted between 7 am - 2 pm MST (UTC-7), which allows more time for the content to be live and assessed by the algorithm before the number of active users drops off overnight. However, the lack of a distinct trend in this plot indicates that post time is but one of many factors that may impact the success of a video. This concept is also not to indicate that the morning MST is the most ideal time to upload, rather that it is the local time of the majority of the audience.
Fig. 6: We will delete this figure.
Lines 215: “Viewer retention” is the common terminology in social media. However, to keep this term consistent with our figures, we will refer to it as the ‘average video view duration (%)’ throughout.
Fig. 7: We will add a more thorough explanation in the text for those that are unfamiliar with metrics used in social media analyses. Traditionally, yes, you would expect to see a relationship between video views and average view duration, as videos with a high avg. view duration are hypothesized to be rewarded within the algorithm and shown to more viewers, thus yielding higher views (particularly on platforms like YouTube). A high average view duration also indicates that the audience is more interested in the video content and that it holds their attention rather than scrolling to the next video, thus providing a useful gauge in how effective the science communication video is. However, because TikTok can support such short videos (~15 s), those videos can very easily yield a high avg. view duration, but that doesn’t necessarily mean they will also have a high number of views. We see videos with the highest number of views (>90,000) have avg. view durations of >40%, indicating that this is the value creators should aim for.
Fig. 8: The higher the engagement rate, the more people are interacting with a piece of content, thus showing higher interest on the side of the viewer (see Habibi and Salim, 2021, another study that measures user engagement of educational science content on TikTok). As is hypothesized with how algorithms work, content that is interacted with more will be shown to more people, thus yielding higher views. What is interesting on this plot is that even videos that did not yield a high number of views still yielded high engagement rates. Here we see no observable trend between number of views and the engagement rate on the content. It could be that a video needs both a high engagement rate and a high avg. view duration to be shown more in the algorithm and receive more views (see Figure 9).
Fig. 9: We find that there is no clear relationship between the average view duration and engagement (two factors that are likely to increase video reach in the algorithm). Thus, just because a person views more of a video does not necessarily mean they are more likely to interact with the content. However, the average view duration here is also linked to the length of the video, as ~15 s videos can much more easily yield a high avg. view duration than can a ~150 s video (Fig. 10–the longest videos actually have consistently high engagement rates, especially for shares).
Section 6.4: Explained in reply to Fig. 7.
Section 7: There is essentially zero transparency to TikTok’s algorithm, hence the importance of this study and others like it. The existing literature related to analyzing content on TikTok and the algorithm is very limited (see Klug et al., 2021, which we will discuss and add a citation for). This study is thus important because it provides additional data and insight for the very little that has been analyzed of science communication on TikTok. We will address in the text that algorithms can change over time, and thus it will be useful to conduct future surveys over time. However, algorithmic changes that fundamentally impact how the app functions are unlikely to occur over short periods of time. 95% of teens in the United States say that they have access to a smartphone (Pew Research Center). Thus there is almost no exclusion to the technology, demonstrating that TikTok has nearly unlimited reach potential. We have addressed audience demographics in previous comments.
Lines 405-412:
- We have addressed these concerns all in previous comments (see comments to Figure 3).
- We do not intend to suggest that every topic be related to a newsworthy event or place-based geology, rather that these are ways in which to maximize the algorithmic impact of the video content, thus reaching the highest amount of viewers and sharing the science with a broad audience. These are also tools to make the topic communicated relevant and relatable to the audience. As we demonstrated, even videos that had lower views yielded high engagement rates, which indicates that the content was still impactful, even if it was received by a smaller audience. We find that demonstration videos < 30 s are an impactful way to communicate topics, as are lecture-style videos ~40 - 120 s in duration. We include this discussion of gender and this recommendation as we hypothesize that there may be inherent sexism baked into the TikTok algorithm, where accounts that are identified as female are shown less or are not shown science-related content on their “For You” page. “The recommendation would be merited if the strategy is to include more gender-related topics to gain more female followers, who then view videos of other topics is precisely what we suggest and recommend. A nuance to note is that videos from an account a person is following are also often shown on the ‘For You’ page. Hence, even if the video is viewed by an account follower, the view will still be counted as coming from the ‘For You’ page.
- We re-emphasize here that views on TikTok generally do not come directly from hashtags (like one might look up a hashtag on Twitter), rather that hashtags are tools to provide additional algorithmic context for the video (especially beneficial if highlighting a location, e.g., #california).
Citation: https://doi.org/10.5194/egusphere-2022-494-AC1
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AC1: 'Reply on RC1', Emily Zawacki, 27 Jul 2022
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RC2: 'Comment on egusphere-2022-494', Anonymous Referee #2, 03 Aug 2022
Dear authors,
First, I would like to congratulate you on the ‘Terra Explore’ initiative. The metrics data shows that Tiktok can be a very promising platform to help geoscience outreach. Also, it explains some important features of TikTok to geoscientists unfamiliar with the platform. Your paper can have a lot of potentials, but it requires major revisions to critically reflect on the empirical data. You need to rethink your argument, research question, methodology, and scholarly contribution to increasing public exposure to and/or effective geoscience communication.
First of all, it’s not clear which research gap this paper tries to address. The goal to increase the visibility of geosciences and geophysics on TikTok is achieved to some extent. The 2 million views in 4 months are impressive, but there is almost no description of why would and how the authors created those very popular videos in such ways. Are there any different considerations when the authors made those videos? Is there any hypothesis that led the authors to make those videos? Or the success videos are simply due to good luck? Above all, what has video creators learned from the process? I think that the authors should reflect on this process from a critical standpoint.
The authors listed two goals in the manuscript: To increase the visibility of geosciences and to determine the best strategies for effective geoscience communication on TikTok. However, the engagement is not discussed thoroughly, and the listed data are insufficient to analyze the geoscience communication's effectiveness on TikTok. Statistics of likes, views, and percentage of watched are useful metrics for showing the engagement of videos on TikTok but more importantly, stemming from the previous point, the authors should give their reasons. Although some design factors have been discussed loosely, like memes and music, the authors may want to give a more clear message about why some of the videos you made are more popular than others (at least your hypotheses and using your data and experiment design to test them). The current analysis and the reported data are not sufficient. I am wondering why the authors did not do any qualitative analysis of comments (considering you have so many comments and some of them are not relevant to learning). Lacking experiment design and the reported data as written hardly can give an insightful answer. I will recommend the authors analyze the contents of the comments and use a mixed method to critically discuss the potential reasons. This leads to another potential weakness: the literature review on how to design geoscience videos to engage the public on social media is insufficient.
Also, the authors may want to do a more thorough literature review about the existing geoscience efforts on TikTok and how your efforts differ from others (again, what research gap this paper tries to address). The current literature review gives a valuable introduction to TikTok for geoscientists and communicators unfamiliar with TikTok, but this is not a research gap. Without this, this manuscript is not a rigorous research inquiry. The authors mentioned several possible theories, such as place-based video design (may want to use field-based or location-based design since the place-based can be misleading to place-based educational design) and geohazard event-based video design. However, there is no literature review about these designs or what is the template of the authors’ video design. Very little is said about how this effort and results extend generalizable knowledge about how communicators can replicate the success of designs.
The authors may want to discuss what their hypothesis works, what may not, and how they predicted the videos' success on TikTok (considering there is no existing formula or clear pattern in the data). How is feedback incorporated into the development of new videos? Although this work shared valuable data to confirm and highlight the possibility of TikTok, especially the unique advantage of FYP and TikTok algorithm for new geoscience communicators, it is not novel enough to consider extending our knowledge boundary about geoscience communication on TikTok.
For example, what are the teaching goals of each video? why do some of the videos get so many views? While some others are not. Is it the content? The narrative? The visuals? The overall design? Why they were recommended more than others? Is it really because of the geohazard feature? If so, the authors should organize their information better. The GVM could be a good visualization, but the evidence is not enough to be convincing. The paper tested several metrics but didn’t show convincing evidence of what factors can increase the visibility of geosciences and geophysics videos. The reported results have no clear pattern to determine what type of videos or design would be more popular. As written, the amount of GVM videos (9 videos) is not enough to discuss the statistical significance of the effectiveness of this design element. This is the same as the geohazard videos. (A minor suggestion: The authors may want to define the ‘lecture-style video’. Is it a universal definition or just for TikTok?)
Moreover, two million views in 4 months with only 48 videos are amazing, but does the views of TikTok comparable to those of YouTube videos? Considering its extremely short durations (5-60sec), a video on the same topic can be much longer. This question also applies to the percentage of watched and the likes. On YouTube, IRIS channels also have many good geohazard videos, but it looks like they didn’t get so many views. Is it the timeliness, the platform, the audiences, or the design? I think the authors have the special advantage in giving a good discussion about this.
Furthermore, the work provides some valuable data. But, many of the figures have little value and may be removed or revised. More importantly, the results alternate between assertions about the evidence presented, point-of-view statements that are not identified, and overreaching claims. For example, Line 278 to 280, “Videos 40 sec to 2 minutes in length received the highest engagement rates (Fig. 10)”, Line 282 to 284 “High engagement rates on videos with lower view counts …a wider audiences..”, I cannot find a clear pattern or empirical evidence supporting these claims.Minor notes:
Line 30-32, 291-299: Interestingly, there is almost no literature review or efforts mentioned or discussion about using YouTube to communicate geosciences (the authors even talked about Twitter in the introduction). Shouldn’t YouTube be a more comparable video-based social media platform to TikTok? Especially considering IRIS, UNAVCO, and Open Topography all have their YouTube channels. Is there a particular reason?Line 60: I think the current limitation for TikTok videos is 10 minutes, not the 3mins anymore.
Literature Review is not enough. As mentioned at the beginning, the literature review introduces some interesting concepts and facts about TikTok and science communication on TikTok. Still, these do not carry over to the study's variables and measurement.
Regarding figure 5, why do you not report the statistics of shares? Have any of your videos been shared and viewed on Twitter or embedded on other websites? How will these be categorized? Will they be categorized into FYP, Personal Profile, or Unknown? This may affect how videos are being found and watched.
Line 350-355: If the gender of audiences on TikTok cannot be accessed or the data is unreliable, then a more thorough discussion of the limitation should be added.
I personally want to see more data about the timing of geohazard events and the release time of videos. Is there any relationship between the speed of release and the views of the video?
The demonstration using food could not be the major reason for different views. One possibility in my mind is the interests of the topic (e.g., more people have motivations in learning the magnitude of an earthquake than the types of faults), is there any useful comments to give insights about this?
The authors may want to clarify how this work contributes to broader theoretical debates like how geohazards affect or how place-based design affects engagements. Current discussions are not critically reflected on the empirical data (including yours and others).
Citation: https://doi.org/10.5194/egusphere-2022-494-RC2 -
AC2: 'Reply on RC2', Emily Zawacki, 26 Aug 2022
We thank this second anonymous reviewer for their time in reviewing our manuscript and for their helpful comments that will improve this work.
First of all, it’s not clear which research gap this paper tries to address…
This study is the very first to produce and evaluate geoscience content on TikTok. TikTok and short-form video content has exploded in popularity, and until this point there had been no research on how to capitalize on this success for geoscience communication efforts. We thus fill a crucial research gap related to science communication efforts via short-form video content and provide the first ever analysis of geoscience content on TikTok. There is no way to predict which videos may go ‘viral’ on TikTok (as is the case for any type of viral content). Virality likely requires some type of luck, but also content resonates with the viewer. Our goal with this study was to produce different types of content (different video length, video topic, presentation style, etc.) and evaluate what trends (if any) we can discern in content that had the highest success in terms of reach and engagement.
The authors listed two goals in the manuscript…
We agree with the reviewer that an included discussion of user comments would be beneficial and strengthen our findings. As we discuss in the section on ethical implications, user privacy on TikTok is an important consideration, and thus we will likely not include any specific comments, as no users gave explicit agreement to be part of this study beyond TikTok’s terms of use. However, we can group comments to categories related to statements like, “That was a cool video,” “I learned something new,” “I have a further question related to this video,” “I know the place that they’re talking about here,” etc. to evaluate the type of user engagement the video receives. Our videos received a total of over 3,500 comments during the study period, so we will concentrate on an analysis of comments for our top ten most viewed videos.
Also, the authors may want to do a more thorough literature review about the existing geoscience efforts on TikTok…
There is no other existing literature related to geoscience communication efforts on TikTok, as ours is the very first study to exist. The majority of geoscience content on TikTok is produced by young individuals who have recently or are currently completing bachelor’s or graduate degrees in the geosciences. Content is often split between “meme-style” videos, showing what’s inside a rock when you break it open, and explainer videos of geology topics. Our organizations are pioneering an effort to produce concerted geoscience education videos on TikTok and encourage more scientists and science communicators to do the same. Our study provides the first knowledge base of what types of geoscience communications videos may be successful on TikTok. While there is no existing literature on the topic, there are many museums that now have TikTok accounts (e.g., the American Museum of Natural History), and an analysis of museum-related content would be complementary to this study, but outside the scope of the current study.
We agree that the term “place-based” can be misleading, so we will change this term to “location-based.”
The authors may want to discuss what their hypothesis works…
There is no singular way to predict the success of a video, and unfortunately there will never be a formula to guarantee success with social media content. However, we have been able to observe certain trends both related to the topic of the video and the ‘construction’ of a video that may aid in its success and increase the impact of the communication effort. For example, after making a video talking about the geology of a specific location that got a large amount of views, we made more videos featuring location-based geology that were also largely successful. As the videos were all made during a pilot period, the pilot was focused on producing various different types of content. After full analysis of the videos (this study), that allows us to fully assess patterns and trends in video success, which can then be incorporated into the development of new videos.
For example, what are the teaching goals of each video? why do some of the videos get so many views? While some others are not…
The teaching goals of each video are essentially to convey geoscience-related information (in our organizations’ case seismology, geodesy, and topography) in a way that is accessible and engaging to the viewer. There unfortunately is no way to specifically discern the exact reason for why a video is successful, as it is likely a combination of factors (the topic + the design/format + the visuals).
Regarding the number of GMV videos, they are restricted to when magnitude 6+ earthquakes occur, so it is generally not possible to get a large sample size of videos over a short period of time. However, even with a smaller sample size, the GMV videos are the best way to isolate variables,as the video design/format, visuals and description are the same, and observe if there are any other factors that may impact the videos’ success.
As a ‘lecture-style’ video is our own definition and wording, we will include a more thorough explanation of what we mean with this term. (Essentially, like a teacher would ‘lecture’ to a class using a PowerPoint presentation, our ‘lecture-style’ videos feature the host directly talking to the audience like a teacher would, showing visuals and imagery in the background.)
Moreover, two million views in 4 months with only 48 videos are amazing, but does the views of TikTok comparable to those of YouTube videos?...
Views on TikTok can be difficult to compare to views on YouTube, as TikTok videos are so much shorter than YouTube videos, as noted by the reviewer. For a few of our TikTok videos, we pulled a number of visuals directly from longer videos on the IRIS and UNAVCO YouTube pages, which would be the best comparison of a long-form vs short-form video. However, it is difficult to directly compare the number of views, as some of the YouTube videos have been up for seven years accumulating views and likely have variable spikes in views over time. A future study could perform a more specific direct evaluation of short-form vs. long-form educational geoscience video content.
The best direct comparisons we can provide for TikTok vs. YouTube as platforms are the Terra Explore lidar TikTok videos that were uploaded to the OpenTopography YouTube channel as ‘YouTube Shorts.’ The same exact videos on YouTube received extremely few views, orders of magnitude lower, compared to the videos on TikTok. This observation would suggest that there is a unique opportunity for expanded reach of science communication topics on TikTok. However, that is beyond the scope of this paper.
Furthermore, the work provides some valuable data..
We have since performed more rigorous statistical analyses per the comments of Reviewer #1, which will better aid in the clarification of such statements.
Minor notes:
Line 30-32, 291-299:
There is little existing literature that we are aware of that discusses geoscience communication on YouTube. However, there is now a study by Wang et al. (2022) in Geoscience Communication that does evaluate geoscience videos on YouTube that we will include in a review. (Please do let us know of any other specific studies you may be familiar with.) While YouTube and TikTok both are video platforms, the short-form, ‘casual’, vertical videos of TikTok and its algorithm-driven nature make them less comparable than at first glance. However, we can include more of a discussion of our organizations’ own efforts on YouTube, which differ quite greatly from the videos produced for TikTok. For example, the OpenTopography YouTube channel primarily features tutorials and webinars geared towards researchers and scientists, rather than direct public outreach efforts. IRIS on their YouTube have videos that range from public outreach (e.g., ‘Women in Geoscience Series’) to educational animations and explainers. UNAVCO’s YouTube channel largely has videos from webinars and short course videos.
Line 60:
TikTok now does allow users to directly upload a singular 10 minute video file within the app or via desktop, however you can only film videos on TikTok that are 3 minutes in length (which is the primary mode of creation).
Literature Review is not enough…
There currently is no other existing literature related to the geosciences on TikTok, and there are very few other studies that evaluate or discuss science communication on TikTok or short-form video. Our study is the very first to create and evaluate geoscience communication on TikTok, and we are pioneering evaluations and investigations rather than drawing upon an existing knowledge base. The analytical toolkit that we use is more generally related to performance of content on social media. We can include a further discussion of the types of geoscience videos on TikTok (primarily produced by individuals who have recently graduated or are currently in bachelor’s or graduate geoscience programs).
Regarding figure 5…
Shares are not reported as a video view category. There is no way to know how or where a video has been shared (copied the link vs. texted to a friend vs. posted to a social platform, etc.). We hypothesize that video views from shares are counted as a ‘Personal Profile’ view, as videos shared are the direct link to the video. Additionally, a video being shared does not equate to a video view, and there is no way to know whether the video was actually viewed when it was shared.
Line 350-355:
We have no reason to believe that the gender percentages reported on TikTok are unreliable. While users do not self-contribute this data, TikTok works to discern gender from accounts that the user links (Facebook, Instagram) where users can report gender, or from algorithmic assessment of user behavior, users’ names, etc. (If anything, TikTok is known for over-mining user data). These are the same demographics that are given to multi-million dollar companies that run targeted advertising campaigns on the app, who would rely on robust demographic data. We do note though that the gender % of followers does not account for non-binary individuals, and what is lacking is a more nuanced catagorization of gender.
I personally want to see more data about the timing of geohazard events…
All videos related to geohazards (primarily earthquake and GMV videos) were released the day of or the day after the event. Thus, there is essentially no lag time that can be analyzed.
The demonstration using food could not be the major reason for different views…
What we suggest in the text is that the difference in the videos’ performance is that one video was ~30 s, and the other video was ~1 min. The significantly longer duration of the video is what we hypothesize led to its smaller reach, suggesting that shorter demonstration videos better capture an audience’s attention.
The authors may want to clarify how this work contributes to broader theoretical debates like how geohazards affect or how place-based design affects engagements..
There is an upcoming abstract from the Geological Society of America 2022 meeting that appears relevant to this point: (doi: 10.1130/abs/2022AM-379409) “It is recommended to practitioners for devising pedagogically-sound lessons on any geology/environmental science-related topic to include using as many recent, real-world incident examples as possible and especially relying on controversial, debatable, and sensational sub-topics (within reason).” We can connect our findings to others like these that observed increased student engagement from teaching topics related to geohazards and location-based geology.
Citation: https://doi.org/10.5194/egusphere-2022-494-AC2
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AC2: 'Reply on RC2', Emily Zawacki, 26 Aug 2022
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-494', Anonymous Referee #1, 06 Jul 2022
Note: My familiarity with Tik Tok is minimal and my experience with it is limited to viewing videos that are occasionally forwarded to me. I am, however, familiar with other media platforms and their use for geoscience communication. Furthermore, I am a geoscientist interested in communication and using emerging platforms like TikTok.
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General comments:
The manuscript presents the TikTok analytics data gathered for 48 educational geoscience videos produced and published between Oktober 2021 and February 2022 on the media platform TikTok. Given TikTok’s increase in popularity as a media platform, exploring its potential as a means for geoscience communication is a very merited undertaking. There are no language issues and it’s easy to follow the text. Unfortunately, the study lacks direction and it’s unclear throughout the manuscript what exactly the authors intend to use the TikTok analytics data for. In other words, there’s no apparent experiment design. This is reflected throughout the manuscript in several ways. These include, but are not restricted to, the following:
1) It’s unclear why some of the x-y relationships are looked at (e.g., average view time and total views) and what the implications of a relationship would be. Many figures are redundant or show no patterns, making them seem like simple “data dumps”. (For example, why show gender ratio over time when it does not change?). In other figures, the authors observe patterns I cannot see (e.g., Fig. 3).
2) The last criticism highlights another major flaw of the study, i.e. the complete lack of statistical analyses that would introduce rigor and objectivity in the detection of relationships and patterns in the data. It is difficult to make specific recommendations for methods at this point since I am unsure about the overall goal and experiment design for the study. Given on what I can infer from the presentation and discussion of results, however, I imagine simple correlation analyses and ANOVAs (with “significance” test ) would be suitable for the largest part.
3) The study includes US-centric assumptions that compromise important take-away messages of the study. E.g. the authors use the MST time zone (a US time zone) not just to communicate their results, but also to define the time of the day. This is done without knowledge of the location of the viewers, who may live in a completely different time zone. Since a large portion of topics are or general interest and TikTok is a global media platform, it’s not unreasonable to assume the reach goes beyond the US. If it does, nothing can be said about the preferred viewing time of the audience or, by extension, the optimal time for upload. This could be avoided by good (/more thoughtful) experiment design.
4) The final conclusions and recommendations are mostly not supported by the study due to several of its flaws, the lack of clear (testable) hypotheses and lack of rigorous testing.
As such, I cannot recommend the manuscript for publication. That said, I appreciate the efforts that go into making educational videos and maintaining a presence on a media platform. With the channel and videos, the authors are on good track to test the effectiveness of TikTok (or aspects of it) and I strongly encourage the authors to do so. However, this will require a clearly thought through study/experiment design. This should include a clear idea of what questions should be addressed with the experiment, what hypotheses are tested, what the metrics are used for testing, etc.. This also includes a clear idea of how data (e.g. TikTok analytics data) can be used in it and what its limits are.
Specific comments:
The title is somewhat misleading. The study does not test the effectiveness of TikTok as a platform for geoscience communication. An important part of effective communication is what happens on the receiving side (e.g., information retention). This study looks solely at reach and basic form of engagement.
Line 16 - The term “retention” is a tad misleading. Until it was explained, I took it as a measure for how much of the video was remembered.
Line 20 – What is the “For You” page? If it’s a page with personal video suggestions, maybe use a more general description of it, such as “suggested viewing page (“For You” page on TikTok)” for those unfamiliar with TikTok. It’s explained in section 2, but I’d use a more explanatory and general term for it in the abstract so it doesn’t require knowledge of TikTok.
Line 22 – “Went the most viral” – I’m aware that such terminology has established itself fairly well by now (among specific demographics at least), but I nevertheless recommend rephrasing that for an audience that is unfamiliar with it yet have an interest in exploring such media platforms as a communication tool.
Lines 53-55 – It’s unclear what the purpose and nature of the analysis is. If it is to determine factors of a video that help maximise reach (line 55), why were engagement and view duration analysed at all? Usually, an introduction outlines the broad questions, goals and hypotheses tackles by a study. This helps guide the reader through the manuscript. At this point, I still don’t know what these are or what analyses were conducted on the 3 metrics and for what specific purpose. (Unfortunately, I also miss clarification of this down the line in the following sections).
Lines 58-77 – I appreciate the introduction to TikTok (section 2) and think it’s important. I would add some comments on TikTok’s reach. Who are the viewers, how are they distributed globally? This may be very important information for communicators who want to target specific communities.
Line 67-68 – This is a tad vague. What are these recommendation algorithms based on exactly? The authors list “user’s profile settings”, “location” and “activity”. Can users choose topics of interests in the profile settings? Since the study’s results are, to a degree, sensitive to this, I think a closer look at it and a more elaborate explanation is warranted. This will also help communicators plan their activities on TikTok better.
Line 77 – It’s unclear what is meant by searching sounds. It reads as though sounds are used as hashtags are. Is that accurate?
Lines 85-93: What is the longevity of such hashtags on TikTok? On twitter, for example, they may rapidly change and quickly lose popularity and reach. Is #LearnOnTikTok ongoing and intended as a “stable” hashtag? Was the associated campaign was a one time event or something ongoing and sustainable? If it’s ongoing and the hashtag serves almost like an education “channel” on TikTok now, this should be communicated. As a communicator, this would be very useful for me then. If it’s not expected to survive long as a hashtag, on the other hand, it doesn’t warrant as much explanation.
Lines 104-105: I disagree with the general statement that geoscience does not lend itself to experiment-based content as much. On the contrary, since geoscience is effectively physics and chemistry applied to the Earth, many classic physics and chemistry experiments can be used to demonstrate how something works on Earth. In atmospheric sciences alone, there are plenty of pressure and moisture experiments that can be conducted (at home) to demonstrate important concepts. On the other hand, for Earthquake science, experiments involving concepts of friction and liquefaction come to mind.
Lines 123-124: Was this by design and are there studies of how the metrics used here (reach, engagement and viewing time) vary depending on the gender of the presenter? Given prevailing differences in perception of scientists of different genders, this may be important information for geoscientists who consider TikTok as a communication platform.
Section 4 (general): It’s unclear what determined the choices in video characteristics and how these choices were made with a specific experiment/goal in mind. This is essentially the “experiment setup” section, but I cannot see how the choices made here serve the testing of a broader hypothesis or help answer the study’s overarching question(s). For example, if one were to determine the optimal video length to maximise the engagement rate, one would vary the factor of interest and reduce the number of other free parameters (such as upload time). Reversely, If I wanted to determine the best time to upload a video, I would vary this parameter and keep others constant. I don’t see this type of experiment-based and hypothesis-guided thinking in this section.
Line 175: Please express time using the primary standard UTC (or list in in brackets). As someone who’s not from North America, I was completely unaware of MST.
Fig.2: I think the text-based summary of views is sufficient. The figure does not show any pattern or provides any valuable additional information and thus seems a tad redundant.
Fig 3: Unless most viewers are known to be from North America and ~ the MST time zone, I would change this to UTC. In fact, if the viewer location does not coincide with the MST zone, discussing times of the day may be misleading. Furthermore, I question the merit of presenting this data at all, since (a) there is no clear pattern except maybe an increase in views towards the evening, and (b) global viewers will likely be spread across different time zones.
Fig. 6: The ratio remains ~constant over time, making the figure rather redundant. It’s sufficient to simply state the ratio, as already done in the text.
Lines 215: Please change the term “retention” to something more intuitive like “view duration”. You use the latter term already. I recommend simply sticking to that, also to avoid confusion with viewer information retention (memory).
Fig. 7: It is unclear why video views is plotted against video “view duration”. Is a relationship expected? Why? What would be the meaning of it?
Fig. 8: See comment on Fig. 7. It’s unclear why views are plotted against engagement rate. What would the discovery of a relationship between these metrics help with? What hypothesis or idea would that address?
Fig. 9: See comment on previous 2 figures. What’s would be the significance of the x-y relationship? Furthermore, the caption does not guide the reader through the figure in any way. It does not explain anything and I am left wondering why it is shown and what the authors would like me to see in it.
Section 6.4: I understand why duration and time posted may be valuable information. These may be useful for communicators in their planning to maximise views. However, I do not see the significance of a relationship between views and average % watched.
Section 7: Any thorough, literature-informed discussion of the study’s limitations (and the limits to recommendations made) is missing. For example, I think it would be important to:
- Comment on importance of different metrics for assessing communication effectiveness.
- Comment on how sensitive the study’s results are to the specific algorithms used by TikTok, how transparent they are and how (often) these may change. How does this affect the take-away messages of this study?
- Comment on technology exclusivity and how it limits reach.
- Comment on the effect of video content on audience demographics/nationality/location. This may be important in context of the interpretation of the viewing times also.
Lines 405-412: I question several of these recommendations (and related conclusions) based on some of the study’s flaws:
(a) The recommendation to post earlier in the day seems based on the discussed relationship between time posted and video views. More precisely, it seems based on the observation that videos that received the most views were uploaded in the morning or early afternoon. By simply looking at the data plot, I do not make the same observation. In fact, it is difficult to see any significant pattern at all except maybe a general increase in video views later in the (MST) day. This contradicts the authors’ findings and highlights the need for rigorous statistics to make sure a signal/observation is real. Furthermore, this recommendation is very US centric and/or vague. To elaborate: The authors use a US time zone to define the time of the day. Does the recommendation pertain to MST morning or morning in whatever time zone the communicator lives? To answer this, the authors need to establish where the views are from. If they could establish (1) that their viewers are US (or MST) based, and (2) that there is an actual relationship between views and time of day, a recommendation for upload time could be merited (albeit restricted to the US). As it is, however, no such conclusions can be drawn from the TikTok analytics data.
(b) As a communicator, I want to communicate a specific set of problems and topics. Recommendations to choose a topic based on what is newsworthy (or tied to a specific location) is therefore questionable. This recommendation seems focused on increasing views (regardless of intended subject of communication) rather than on effective communication of a specific topic. The recommendation to include gender-related topics is similarly problematic. I would like to know “What do I do to increase the number of female viewers for videos about this specific topic?” and not “What topic should I choose to increase the number of female viewers.” The recommendation would be merited if the strategy is to include more gender-related topics to gain more female followers, who then view videos of other topics. However, this strategy is also questionable given that relatively few views are gathered from “following” (Fig. 5).
(c) Given how few views the videos got from hashtags (I cannot even see the percentage of it for most of Fig. 5) I do not see how the authors can list this as a recommendation here.
Citation: https://doi.org/10.5194/egusphere-2022-494-RC1 -
AC1: 'Reply on RC1', Emily Zawacki, 27 Jul 2022
We thank the reviewer for their time and helpful comments regarding our manuscript. We believe that with the described additions below to better explain our study, particularly for those that are unfamiliar with TikTok or similar social media analyses, our manuscript will be suitable for publication and of significant value to the science communication community.
Given the total opacity of the TikTok algorithm, our study seeks to elucidate patterns and trends related to reach and engagement of geoscience content on TikTok so that science communicators can find the most success there. More so than any other social media platform, content discovery on TikTok is algorithmically-driven, and our study uses all analytical data metrics available on TikTok to provide insight relevant for science communicators. We specifically analyze (1) reach [video views], (2) video view duration, and (3) video engagement in assessing the impact of each video. We seek to maximize all three factors: (1) videos seen by more people increase the audience impacted by the content, (2) the longer people view a video indicates greater interest in the video and subject, and (3) engaging with the video (like, comment, share) demonstrates additional interest in the video and subject, all reflective of successful science communication.
The videos we created for the Terra Explore TikTok were part of a pilot project to test producing geoscience video content on TikTok. As such, we aimed to produce videos of various topics/styles, durations, with different hashtags used, and different posting times/dates in order to sample parameter space. Although there was not a systematic design to every video, these videos still provide important insight and much needed data for science communication efforts on TikTok. As it is difficult to isolate singular variables, we use the similarity of content and format in GMV (ground motion visualization) videos to more clearly evaluate individual factors. We acknowledge that algorithms may change over time as platforms evolve, but we are not aware of evidence that TikTok is changing its algorithm so rapidly as to invalidate attempts at analysis.
- We survey all available data metrics from TikTok to discern any notable trends in video reach and engagement, as is common with research examining content on social media platforms (see Habibi and Salim, 2021 and Wang et al., 2022 (Geoscience Communication)). We will more specifically describe the purpose of each parameter that we are looking at and what it indicates, as well as our associated hypothesis with how it relates to algorithmic discovery. As an example, social media algorithms are generally believed to reward videos that have a high viewer retention (how long someone watches the video) and high engagement rate by showing the video to more people (as these videos keep users engaged and on the app/platform for longer) (Klug et al., 2021). However, short videos on TikTok (~15s) can very easily yield high viewer retention rates, which doesn’t necessarily translate to high views or engagement. Understanding the data related to each metric is thus important in deciphering what characteristics are likely to make a successful video. Beyond understanding the algorithm itself, a high average view duration and a high engagement rate indicates that the audience is interested and invested in the video content and are extremely useful metrics for evaluating how engaging and successful the video content is.
We will remove the figure depicting gender of followers over time, as a text explanation will suffice.
- We strongly agree that statistical analysis is needed in this study and will greatly strengthen our analyses. We are working on performing correlation analyses for all the relationships we evaluate (including r, r2, and p values to determine statistical significance).
- TikTok provides information about the top territories of an account’s followers and individual video views by region. ~85% of the Terra Explore account’s followers and views are from the United States, which is why we defaulted to a more US-centric view. However, we will include this information related to viewer/follower region and will analyze any videos that have a significant proportion of views from outside the US. We hypothesize that TikTok heavily mines data based on a user’s location and often shows video content local to that viewer. Post time optimization is typically linked to the location where the majority of your audience is, and hence would apply to ‘local morning’ vs ‘local evening.’
- While our videos posted were part of a pilot, we believe that they provide useful information for science communicators, especially given how limited any existing studies of science communication on TikTok are and how untapped the potential of TikTok is.
We will adjust the title of the manuscript so that it more accurately reflects the content.
Line 16: “Viewer retention” (also ‘audience retention’) is a standard metric in social media for the average percentage of a video people watch. However, to keep this term consistent with our figures, we will refer to it as the ‘average video view duration (%)’ throughout.
Line 20: The “For You” page is the Proper Noun name for this feed on TikTok. In the abstract, we define it as “TikTok’s algorithmic recommendation feed.”
Line 22: We will qualify ‘viral’ as high views and engagement.
Lines 53-55: As described in point 1, we will more thoroughly outline our methodology and describe the importance of each metric we analyze. We analyze engagement, as videos with high engagement are hypothesized to be rewarded by the algorithm and will continue to be shown to more people. This cycle of increased engagement and reach thus increases the impact potential of the science content. High engagement rates also indicate an increased interest from the viewer in the video, demonstrating the impact and ‘success’ of the video.
Lines 58-77: We can include additional context regarding the global distribution of TikTok users.
Line 67-68: TikTok provides no information regarding their AI algorithm or how it works, hence why studies like this are important. The information we provide in this section is essentially the extent of all information TikTok publicly makes available. Users can indicate they are ‘not interested’ in a video, but there is no way to choose topics of interest other than watching videos on the app (or skipping them) and liking videos that they enjoy.
Line 77: We recommend downloading TikTok for a brief user experience. Sounds are background audio clips that can be re-used by multiple users and are separate from hashtags.
Lines 85-93: The lifetime of a TikTok hashtag is essentially infinite. You can click on a hashtag and see all videos that have ever been created that use that hashtag. Any person can use any hashtag at any time. As we discuss later in the paper, hashtags on TikTok have a fundamentally different ‘function’ than they do on platforms like Twitter. People generally do not ‘search’ for hashtags on TikTok like they do on Twitter. We hypothesize that hashtags are primarily used in TikTok’s AI to provide additional information and context for the video when deciding who to show it to with the algorithm.
Lines 104-105: We do not say that it is impossible to have experiment videos related to geosciences, merely that they are generally less common and/or easy to produce compared to videos of chemistry and physics experiments. A survey of educational science content on TikTok demonstrates an abundance of videos of chemistry and physics experiments and near total absence of geology-related experiments (which we find is more so related to the ease with which at home or classroom chemistry/physics experiments can be filmed and shared on the app).
Lines 123-124: The video presenters are the existing communications staff at our respective organizations. The male presenter was only able to create two videos during this duration, hence we are unable to analyze video metrics based on the gender of presenter, although this is work we would like to do in the future.
Section 4 (general): As it is very difficult to vary just a singular variable when creating TikTok videos, we use the GMV (ground motion visualization) videos as a way to most clearly isolate variable trends with posting. All the Terra Explore videos were created during a pilot project, in which the goal was to test and produce different types of geoscience content on TikTok (different topics, durations, hashtags used, time and day posted, etc.). Although there was not a systematic design behind every single video posted, that does not make the analyses of these videos any less meaningful.
Line 175: We will include UTC with our time zones.
Fig.2: We will delete this figure.
Fig 3: ~85% of viewers of Terra Explore are within the United States, hence the majority of views come from ‘local’ time zones. The concept of post time upload is related to optimizing the upload of your content for when the majority of users/followers will be active on the app so that it is seen by the highest number of people. All our most highly viewed videos (>90,000 views) were posted between 7 am - 2 pm MST (UTC-7), which allows more time for the content to be live and assessed by the algorithm before the number of active users drops off overnight. However, the lack of a distinct trend in this plot indicates that post time is but one of many factors that may impact the success of a video. This concept is also not to indicate that the morning MST is the most ideal time to upload, rather that it is the local time of the majority of the audience.
Fig. 6: We will delete this figure.
Lines 215: “Viewer retention” is the common terminology in social media. However, to keep this term consistent with our figures, we will refer to it as the ‘average video view duration (%)’ throughout.
Fig. 7: We will add a more thorough explanation in the text for those that are unfamiliar with metrics used in social media analyses. Traditionally, yes, you would expect to see a relationship between video views and average view duration, as videos with a high avg. view duration are hypothesized to be rewarded within the algorithm and shown to more viewers, thus yielding higher views (particularly on platforms like YouTube). A high average view duration also indicates that the audience is more interested in the video content and that it holds their attention rather than scrolling to the next video, thus providing a useful gauge in how effective the science communication video is. However, because TikTok can support such short videos (~15 s), those videos can very easily yield a high avg. view duration, but that doesn’t necessarily mean they will also have a high number of views. We see videos with the highest number of views (>90,000) have avg. view durations of >40%, indicating that this is the value creators should aim for.
Fig. 8: The higher the engagement rate, the more people are interacting with a piece of content, thus showing higher interest on the side of the viewer (see Habibi and Salim, 2021, another study that measures user engagement of educational science content on TikTok). As is hypothesized with how algorithms work, content that is interacted with more will be shown to more people, thus yielding higher views. What is interesting on this plot is that even videos that did not yield a high number of views still yielded high engagement rates. Here we see no observable trend between number of views and the engagement rate on the content. It could be that a video needs both a high engagement rate and a high avg. view duration to be shown more in the algorithm and receive more views (see Figure 9).
Fig. 9: We find that there is no clear relationship between the average view duration and engagement (two factors that are likely to increase video reach in the algorithm). Thus, just because a person views more of a video does not necessarily mean they are more likely to interact with the content. However, the average view duration here is also linked to the length of the video, as ~15 s videos can much more easily yield a high avg. view duration than can a ~150 s video (Fig. 10–the longest videos actually have consistently high engagement rates, especially for shares).
Section 6.4: Explained in reply to Fig. 7.
Section 7: There is essentially zero transparency to TikTok’s algorithm, hence the importance of this study and others like it. The existing literature related to analyzing content on TikTok and the algorithm is very limited (see Klug et al., 2021, which we will discuss and add a citation for). This study is thus important because it provides additional data and insight for the very little that has been analyzed of science communication on TikTok. We will address in the text that algorithms can change over time, and thus it will be useful to conduct future surveys over time. However, algorithmic changes that fundamentally impact how the app functions are unlikely to occur over short periods of time. 95% of teens in the United States say that they have access to a smartphone (Pew Research Center). Thus there is almost no exclusion to the technology, demonstrating that TikTok has nearly unlimited reach potential. We have addressed audience demographics in previous comments.
Lines 405-412:
- We have addressed these concerns all in previous comments (see comments to Figure 3).
- We do not intend to suggest that every topic be related to a newsworthy event or place-based geology, rather that these are ways in which to maximize the algorithmic impact of the video content, thus reaching the highest amount of viewers and sharing the science with a broad audience. These are also tools to make the topic communicated relevant and relatable to the audience. As we demonstrated, even videos that had lower views yielded high engagement rates, which indicates that the content was still impactful, even if it was received by a smaller audience. We find that demonstration videos < 30 s are an impactful way to communicate topics, as are lecture-style videos ~40 - 120 s in duration. We include this discussion of gender and this recommendation as we hypothesize that there may be inherent sexism baked into the TikTok algorithm, where accounts that are identified as female are shown less or are not shown science-related content on their “For You” page. “The recommendation would be merited if the strategy is to include more gender-related topics to gain more female followers, who then view videos of other topics is precisely what we suggest and recommend. A nuance to note is that videos from an account a person is following are also often shown on the ‘For You’ page. Hence, even if the video is viewed by an account follower, the view will still be counted as coming from the ‘For You’ page.
- We re-emphasize here that views on TikTok generally do not come directly from hashtags (like one might look up a hashtag on Twitter), rather that hashtags are tools to provide additional algorithmic context for the video (especially beneficial if highlighting a location, e.g., #california).
Citation: https://doi.org/10.5194/egusphere-2022-494-AC1
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AC1: 'Reply on RC1', Emily Zawacki, 27 Jul 2022
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RC2: 'Comment on egusphere-2022-494', Anonymous Referee #2, 03 Aug 2022
Dear authors,
First, I would like to congratulate you on the ‘Terra Explore’ initiative. The metrics data shows that Tiktok can be a very promising platform to help geoscience outreach. Also, it explains some important features of TikTok to geoscientists unfamiliar with the platform. Your paper can have a lot of potentials, but it requires major revisions to critically reflect on the empirical data. You need to rethink your argument, research question, methodology, and scholarly contribution to increasing public exposure to and/or effective geoscience communication.
First of all, it’s not clear which research gap this paper tries to address. The goal to increase the visibility of geosciences and geophysics on TikTok is achieved to some extent. The 2 million views in 4 months are impressive, but there is almost no description of why would and how the authors created those very popular videos in such ways. Are there any different considerations when the authors made those videos? Is there any hypothesis that led the authors to make those videos? Or the success videos are simply due to good luck? Above all, what has video creators learned from the process? I think that the authors should reflect on this process from a critical standpoint.
The authors listed two goals in the manuscript: To increase the visibility of geosciences and to determine the best strategies for effective geoscience communication on TikTok. However, the engagement is not discussed thoroughly, and the listed data are insufficient to analyze the geoscience communication's effectiveness on TikTok. Statistics of likes, views, and percentage of watched are useful metrics for showing the engagement of videos on TikTok but more importantly, stemming from the previous point, the authors should give their reasons. Although some design factors have been discussed loosely, like memes and music, the authors may want to give a more clear message about why some of the videos you made are more popular than others (at least your hypotheses and using your data and experiment design to test them). The current analysis and the reported data are not sufficient. I am wondering why the authors did not do any qualitative analysis of comments (considering you have so many comments and some of them are not relevant to learning). Lacking experiment design and the reported data as written hardly can give an insightful answer. I will recommend the authors analyze the contents of the comments and use a mixed method to critically discuss the potential reasons. This leads to another potential weakness: the literature review on how to design geoscience videos to engage the public on social media is insufficient.
Also, the authors may want to do a more thorough literature review about the existing geoscience efforts on TikTok and how your efforts differ from others (again, what research gap this paper tries to address). The current literature review gives a valuable introduction to TikTok for geoscientists and communicators unfamiliar with TikTok, but this is not a research gap. Without this, this manuscript is not a rigorous research inquiry. The authors mentioned several possible theories, such as place-based video design (may want to use field-based or location-based design since the place-based can be misleading to place-based educational design) and geohazard event-based video design. However, there is no literature review about these designs or what is the template of the authors’ video design. Very little is said about how this effort and results extend generalizable knowledge about how communicators can replicate the success of designs.
The authors may want to discuss what their hypothesis works, what may not, and how they predicted the videos' success on TikTok (considering there is no existing formula or clear pattern in the data). How is feedback incorporated into the development of new videos? Although this work shared valuable data to confirm and highlight the possibility of TikTok, especially the unique advantage of FYP and TikTok algorithm for new geoscience communicators, it is not novel enough to consider extending our knowledge boundary about geoscience communication on TikTok.
For example, what are the teaching goals of each video? why do some of the videos get so many views? While some others are not. Is it the content? The narrative? The visuals? The overall design? Why they were recommended more than others? Is it really because of the geohazard feature? If so, the authors should organize their information better. The GVM could be a good visualization, but the evidence is not enough to be convincing. The paper tested several metrics but didn’t show convincing evidence of what factors can increase the visibility of geosciences and geophysics videos. The reported results have no clear pattern to determine what type of videos or design would be more popular. As written, the amount of GVM videos (9 videos) is not enough to discuss the statistical significance of the effectiveness of this design element. This is the same as the geohazard videos. (A minor suggestion: The authors may want to define the ‘lecture-style video’. Is it a universal definition or just for TikTok?)
Moreover, two million views in 4 months with only 48 videos are amazing, but does the views of TikTok comparable to those of YouTube videos? Considering its extremely short durations (5-60sec), a video on the same topic can be much longer. This question also applies to the percentage of watched and the likes. On YouTube, IRIS channels also have many good geohazard videos, but it looks like they didn’t get so many views. Is it the timeliness, the platform, the audiences, or the design? I think the authors have the special advantage in giving a good discussion about this.
Furthermore, the work provides some valuable data. But, many of the figures have little value and may be removed or revised. More importantly, the results alternate between assertions about the evidence presented, point-of-view statements that are not identified, and overreaching claims. For example, Line 278 to 280, “Videos 40 sec to 2 minutes in length received the highest engagement rates (Fig. 10)”, Line 282 to 284 “High engagement rates on videos with lower view counts …a wider audiences..”, I cannot find a clear pattern or empirical evidence supporting these claims.Minor notes:
Line 30-32, 291-299: Interestingly, there is almost no literature review or efforts mentioned or discussion about using YouTube to communicate geosciences (the authors even talked about Twitter in the introduction). Shouldn’t YouTube be a more comparable video-based social media platform to TikTok? Especially considering IRIS, UNAVCO, and Open Topography all have their YouTube channels. Is there a particular reason?Line 60: I think the current limitation for TikTok videos is 10 minutes, not the 3mins anymore.
Literature Review is not enough. As mentioned at the beginning, the literature review introduces some interesting concepts and facts about TikTok and science communication on TikTok. Still, these do not carry over to the study's variables and measurement.
Regarding figure 5, why do you not report the statistics of shares? Have any of your videos been shared and viewed on Twitter or embedded on other websites? How will these be categorized? Will they be categorized into FYP, Personal Profile, or Unknown? This may affect how videos are being found and watched.
Line 350-355: If the gender of audiences on TikTok cannot be accessed or the data is unreliable, then a more thorough discussion of the limitation should be added.
I personally want to see more data about the timing of geohazard events and the release time of videos. Is there any relationship between the speed of release and the views of the video?
The demonstration using food could not be the major reason for different views. One possibility in my mind is the interests of the topic (e.g., more people have motivations in learning the magnitude of an earthquake than the types of faults), is there any useful comments to give insights about this?
The authors may want to clarify how this work contributes to broader theoretical debates like how geohazards affect or how place-based design affects engagements. Current discussions are not critically reflected on the empirical data (including yours and others).
Citation: https://doi.org/10.5194/egusphere-2022-494-RC2 -
AC2: 'Reply on RC2', Emily Zawacki, 26 Aug 2022
We thank this second anonymous reviewer for their time in reviewing our manuscript and for their helpful comments that will improve this work.
First of all, it’s not clear which research gap this paper tries to address…
This study is the very first to produce and evaluate geoscience content on TikTok. TikTok and short-form video content has exploded in popularity, and until this point there had been no research on how to capitalize on this success for geoscience communication efforts. We thus fill a crucial research gap related to science communication efforts via short-form video content and provide the first ever analysis of geoscience content on TikTok. There is no way to predict which videos may go ‘viral’ on TikTok (as is the case for any type of viral content). Virality likely requires some type of luck, but also content resonates with the viewer. Our goal with this study was to produce different types of content (different video length, video topic, presentation style, etc.) and evaluate what trends (if any) we can discern in content that had the highest success in terms of reach and engagement.
The authors listed two goals in the manuscript…
We agree with the reviewer that an included discussion of user comments would be beneficial and strengthen our findings. As we discuss in the section on ethical implications, user privacy on TikTok is an important consideration, and thus we will likely not include any specific comments, as no users gave explicit agreement to be part of this study beyond TikTok’s terms of use. However, we can group comments to categories related to statements like, “That was a cool video,” “I learned something new,” “I have a further question related to this video,” “I know the place that they’re talking about here,” etc. to evaluate the type of user engagement the video receives. Our videos received a total of over 3,500 comments during the study period, so we will concentrate on an analysis of comments for our top ten most viewed videos.
Also, the authors may want to do a more thorough literature review about the existing geoscience efforts on TikTok…
There is no other existing literature related to geoscience communication efforts on TikTok, as ours is the very first study to exist. The majority of geoscience content on TikTok is produced by young individuals who have recently or are currently completing bachelor’s or graduate degrees in the geosciences. Content is often split between “meme-style” videos, showing what’s inside a rock when you break it open, and explainer videos of geology topics. Our organizations are pioneering an effort to produce concerted geoscience education videos on TikTok and encourage more scientists and science communicators to do the same. Our study provides the first knowledge base of what types of geoscience communications videos may be successful on TikTok. While there is no existing literature on the topic, there are many museums that now have TikTok accounts (e.g., the American Museum of Natural History), and an analysis of museum-related content would be complementary to this study, but outside the scope of the current study.
We agree that the term “place-based” can be misleading, so we will change this term to “location-based.”
The authors may want to discuss what their hypothesis works…
There is no singular way to predict the success of a video, and unfortunately there will never be a formula to guarantee success with social media content. However, we have been able to observe certain trends both related to the topic of the video and the ‘construction’ of a video that may aid in its success and increase the impact of the communication effort. For example, after making a video talking about the geology of a specific location that got a large amount of views, we made more videos featuring location-based geology that were also largely successful. As the videos were all made during a pilot period, the pilot was focused on producing various different types of content. After full analysis of the videos (this study), that allows us to fully assess patterns and trends in video success, which can then be incorporated into the development of new videos.
For example, what are the teaching goals of each video? why do some of the videos get so many views? While some others are not…
The teaching goals of each video are essentially to convey geoscience-related information (in our organizations’ case seismology, geodesy, and topography) in a way that is accessible and engaging to the viewer. There unfortunately is no way to specifically discern the exact reason for why a video is successful, as it is likely a combination of factors (the topic + the design/format + the visuals).
Regarding the number of GMV videos, they are restricted to when magnitude 6+ earthquakes occur, so it is generally not possible to get a large sample size of videos over a short period of time. However, even with a smaller sample size, the GMV videos are the best way to isolate variables,as the video design/format, visuals and description are the same, and observe if there are any other factors that may impact the videos’ success.
As a ‘lecture-style’ video is our own definition and wording, we will include a more thorough explanation of what we mean with this term. (Essentially, like a teacher would ‘lecture’ to a class using a PowerPoint presentation, our ‘lecture-style’ videos feature the host directly talking to the audience like a teacher would, showing visuals and imagery in the background.)
Moreover, two million views in 4 months with only 48 videos are amazing, but does the views of TikTok comparable to those of YouTube videos?...
Views on TikTok can be difficult to compare to views on YouTube, as TikTok videos are so much shorter than YouTube videos, as noted by the reviewer. For a few of our TikTok videos, we pulled a number of visuals directly from longer videos on the IRIS and UNAVCO YouTube pages, which would be the best comparison of a long-form vs short-form video. However, it is difficult to directly compare the number of views, as some of the YouTube videos have been up for seven years accumulating views and likely have variable spikes in views over time. A future study could perform a more specific direct evaluation of short-form vs. long-form educational geoscience video content.
The best direct comparisons we can provide for TikTok vs. YouTube as platforms are the Terra Explore lidar TikTok videos that were uploaded to the OpenTopography YouTube channel as ‘YouTube Shorts.’ The same exact videos on YouTube received extremely few views, orders of magnitude lower, compared to the videos on TikTok. This observation would suggest that there is a unique opportunity for expanded reach of science communication topics on TikTok. However, that is beyond the scope of this paper.
Furthermore, the work provides some valuable data..
We have since performed more rigorous statistical analyses per the comments of Reviewer #1, which will better aid in the clarification of such statements.
Minor notes:
Line 30-32, 291-299:
There is little existing literature that we are aware of that discusses geoscience communication on YouTube. However, there is now a study by Wang et al. (2022) in Geoscience Communication that does evaluate geoscience videos on YouTube that we will include in a review. (Please do let us know of any other specific studies you may be familiar with.) While YouTube and TikTok both are video platforms, the short-form, ‘casual’, vertical videos of TikTok and its algorithm-driven nature make them less comparable than at first glance. However, we can include more of a discussion of our organizations’ own efforts on YouTube, which differ quite greatly from the videos produced for TikTok. For example, the OpenTopography YouTube channel primarily features tutorials and webinars geared towards researchers and scientists, rather than direct public outreach efforts. IRIS on their YouTube have videos that range from public outreach (e.g., ‘Women in Geoscience Series’) to educational animations and explainers. UNAVCO’s YouTube channel largely has videos from webinars and short course videos.
Line 60:
TikTok now does allow users to directly upload a singular 10 minute video file within the app or via desktop, however you can only film videos on TikTok that are 3 minutes in length (which is the primary mode of creation).
Literature Review is not enough…
There currently is no other existing literature related to the geosciences on TikTok, and there are very few other studies that evaluate or discuss science communication on TikTok or short-form video. Our study is the very first to create and evaluate geoscience communication on TikTok, and we are pioneering evaluations and investigations rather than drawing upon an existing knowledge base. The analytical toolkit that we use is more generally related to performance of content on social media. We can include a further discussion of the types of geoscience videos on TikTok (primarily produced by individuals who have recently graduated or are currently in bachelor’s or graduate geoscience programs).
Regarding figure 5…
Shares are not reported as a video view category. There is no way to know how or where a video has been shared (copied the link vs. texted to a friend vs. posted to a social platform, etc.). We hypothesize that video views from shares are counted as a ‘Personal Profile’ view, as videos shared are the direct link to the video. Additionally, a video being shared does not equate to a video view, and there is no way to know whether the video was actually viewed when it was shared.
Line 350-355:
We have no reason to believe that the gender percentages reported on TikTok are unreliable. While users do not self-contribute this data, TikTok works to discern gender from accounts that the user links (Facebook, Instagram) where users can report gender, or from algorithmic assessment of user behavior, users’ names, etc. (If anything, TikTok is known for over-mining user data). These are the same demographics that are given to multi-million dollar companies that run targeted advertising campaigns on the app, who would rely on robust demographic data. We do note though that the gender % of followers does not account for non-binary individuals, and what is lacking is a more nuanced catagorization of gender.
I personally want to see more data about the timing of geohazard events…
All videos related to geohazards (primarily earthquake and GMV videos) were released the day of or the day after the event. Thus, there is essentially no lag time that can be analyzed.
The demonstration using food could not be the major reason for different views…
What we suggest in the text is that the difference in the videos’ performance is that one video was ~30 s, and the other video was ~1 min. The significantly longer duration of the video is what we hypothesize led to its smaller reach, suggesting that shorter demonstration videos better capture an audience’s attention.
The authors may want to clarify how this work contributes to broader theoretical debates like how geohazards affect or how place-based design affects engagements..
There is an upcoming abstract from the Geological Society of America 2022 meeting that appears relevant to this point: (doi: 10.1130/abs/2022AM-379409) “It is recommended to practitioners for devising pedagogically-sound lessons on any geology/environmental science-related topic to include using as many recent, real-world incident examples as possible and especially relying on controversial, debatable, and sensational sub-topics (within reason).” We can connect our findings to others like these that observed increased student engagement from teaching topics related to geohazards and location-based geology.
Citation: https://doi.org/10.5194/egusphere-2022-494-AC2
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AC2: 'Reply on RC2', Emily Zawacki, 26 Aug 2022
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Terra Explore. We produced 48 educational geoscience videos and evaluated each video’s performance. Our most-viewed videos received nearly all of their views from TikTok’s algorithmic recommendation feed, and the videos that received the most views were related to a recent newsworthy event (e.g., earthquake) or explained the geology of a recognizable area.
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Emily E. Zawacki
Wendy Bohon
Scott Johnson
Donna J. Charlevoix
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