Lecture Notes in Education Psychology and Public Media

- The Open Access Proceedings Series for Conferences


Lecture Notes in Education Psychology and Public Media

Vol. 21, 20 November 2023


Open Access | Article

Prevailing ‘Negative Communities’ Online: Algorithmic Influence and User Self-awareness

Junting Ma * 1 , Zihan Ni 2 , Bingfeng Yang 3
1 Xi’an International Studies University
2 Nanjing University of Posts and Telecommunications
3 McMaster University

* Author to whom correspondence should be addressed.

Advances in Humanities Research, Vol. 21, 130-136
Published 20 November 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Junting Ma, Zihan Ni, Bingfeng Yang. Prevailing ‘Negative Communities’ Online: Algorithmic Influence and User Self-awareness. LNEP (2023) Vol. 21: 130-136. DOI: 10.54254/2753-7048/21/20230105.

Abstract

In recent years, the proliferation of short videos imbued with negative sentiment on TikTok has elicited widespread societal attention. This paper investigates the dissemination of negative emotional content on the social media platform TikTok. Specifically, this paper analyzes user data from several short video platforms, including TikTok, and finds that users aged 18-35 constitute the primary audience for short video content. Amid the propagation of negative emotions, this paper proposes the research hypothesis of a “negative community.” It conducts an in-depth exploration of the following queries: 1) Is the algorithm of TikTok complicit in the spread of negative sentiment? 2) Has this dissemination cultivated unique cultural communication attributes, coalescing into a community-based audience? Moreover, 3) In forming and proliferating negative sentiment, which plays a more significant role— the algorithm or the user.

Keywords

negative emotion, community group, TikTok, algorithm mechanism, user behavior

References

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the International Conference on Global Politics and Socio-Humanities
ISBN (Print)
978-1-83558-121-6
ISBN (Online)
978-1-83558-122-3
Published Date
20 November 2023
Series
Lecture Notes in Education Psychology and Public Media
ISSN (Print)
2753-7048
ISSN (Online)
2753-7056
DOI
10.54254/2753-7048/21/20230105
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated