Reposting “till Albert Einstein is TikTok famous”:  The Memetic Construction of Science on TikTok

Zeng, Jing; Schäfer, Mike S.; Allgaier, Joachim

doi:10.31219/osf.io/8tdvm

Cited by 29 publications

(30 citation statements)

References 38 publications

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“…User-centered qualitative studies of TikTok have mostly applied content analysis [31,33,57] or cognitive walkthrough methods [7,30] to reconstruct user experiences with the app. Only very few studies on TikTok (or its Chinese version, Douyin) have investigated users' understanding of or lay theories about the app algorithm.…”

Section: How Users Actually Experience the Tiktok Algorithmmentioning

confidence: 99%

Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm

Klug

Qin

Evans

et al. 2021

13th ACM Web Science Conference 2021

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The short-form video sharing app TikTok is characterized by contentbased interactions that largely depend on individually customized video feeds curated by the app's recommendation algorithm. Algorithms are generally invisible mechanisms within socio-technical systems that can influence how we perceive online and offline reality, and how we interact with each other. Based on experiences from consuming and creating videos, users develop assumptions about how the TikTok algorithm might work, and about how to trick and please the algorithm to make their videos trend so it pushes them to other users' 'for you' pages. We conducted 28 qualitative interviews with TikTok users and identified three main criteria they assume influence the platform's algorithm: video engagement, posting time, and adding and piling up hashtags. We then collected 300,617 videos from the TikTok trending section and performed a series of data exploration and analysis to test these user assumption by determining criteria for trending videos. Our data analysis confirms that higher video engagement through comments, likes, and shares leads to a higher chance of the algorithm pushing a video to the trending section. We also find that posting videos at certain times increases the chances of it trending and reaching higher popularity. In contrast, the highly common assumption that using trending hashtags, algorithm related hashtags (e.g. #fyp, #foryou), and piling up trending hashtags would significantly push videos to the trending section was found not applicable. Our results contribute to existing research on user understanding of social media algorithms using TikTok as an example for a short-video app that is explicitly built around algorithmic content recommendation. Our results provide a broader perspective on user beliefs and behavior in the context of socio-technical systems and social media content creation and consumption.

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Section: How Users Actually Experience the Tiktok Algorithmmentioning

confidence: 99%

Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm

Klug

Qin

Evans

et al. 2021

13th ACM Web Science Conference 2021

View full text Add to dashboard Cite

show abstract

“…Like all other social platforms, TikTok also has positive and negative behaviors. For example, in Zeng et al (2020) the authors analyze the role of TikTok in stimulating science memes. In Hayes et al (2020), the authors illustrate the use of TikTok in facilitating scientific public engagement and contextualization of chemistry.…”

Section: Related Literaturementioning

confidence: 99%

Extracting time patterns from the lifespans of TikTok challenges to characterize non-dangerous and dangerous ones

Bonifazi

Cecchini

Corradini

et al. 2022

Soc. Netw. Anal. Min.

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One of the key aspects that distinguish TikTok from other social media is the presence of challenges. A challenge is a kind of competition that starts when a user posts a video with certain actions and a certain hashtag and invites other users to replicate the same video in their own way. Most challenges are fun and harmless, but sometimes dangerous challenges are launched as well. The authors of these challenges use various tricks to bypass TikTok’s controls. In this paper, we analyze the lifespans of some TikTok challenges and show how they are very different for non-dangerous and dangerous ones. Then, we deepen our analysis by identifying some time patterns that characterize the two types of challenges. Finally, we test the accuracy of the results obtained on a large set of challenges different from those used during the detection of time patterns. The focus of this paper is the detection of time patterns allowing the classification of challenges in dangerous and non-dangerous ones. This could represent a first step towards an approach for the early detection of dangerous challenges in TikTok.

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“…To understand how the TikTok algorithm is imagined by “ordinary users” of the app, we first need to understand how the app is used by them. There are many things that one could use TikTok for, such as creating and sharing content, connecting with like-minded people, participating in public discourse, or simply staying in touch with friends and family (many of these uses have been discussed in existing TikTok scholarship by Abidin, 2020; Boffone, 2021; Kaye et al, 2021; Literat & Kligler-Vilenchick, 2021; or Zeng et al, 2021; among others). Yet, none of my participants really used TikTok for these reasons or in such ways.…”

Section: The Algorithmic Imaginary Of Tiktokmentioning

confidence: 99%

Theorizing “Stories About Algorithms” as a Mechanism in the Formation and Maintenance of Algorithmic Imaginaries

Schellewald

2022

Social Media + Society

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In this article, I report from an ethnographic investigation into young adult users of the popular short-video app TikTok. More specifically, I discuss their experience of TikTok’s algorithmic content feed, or so-called “For You Page.” Like many other personalized online environments today, the For You Page is marked by the tension of being a mechanism of digital surveillance and affective control, yet also a source of entertainment and pleasure. Focusing on people’s sense-making practices, especially in relation to stories about the TikTok algorithm, the article approaches the discursive repertoire that underpins people’s negotiation of this tension. Doing so, I theorize the role and relevance of “stories about algorithms” within the context of algorithmic imaginaries as activating users in sense-making processes about their algorithmic entanglements.

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Reposting “till Albert Einstein is TikTok famous”: The Memetic Construction of Science on TikTok

Cited by 29 publications

References 38 publications

Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm

Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm

Extracting time patterns from the lifespans of TikTok challenges to characterize non-dangerous and dangerous ones

Theorizing “Stories About Algorithms” as a Mechanism in the Formation and Maintenance of Algorithmic Imaginaries

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