Analyzing User Engagement with TikTok's Short Format Video Recommendations using Data Donations-Reference-Cited by-同舟云学术

Analyzing User Engagement with TikTok's Short Format Video Recommendations using Data Donations

Published:2024-05-11 Issue: Volume: Page:1-16
ISSN:
Container-title:Proceedings of the CHI Conference on Human Factors in Computing Systems
language:
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Author:

Zannettou Savvas¹^ORCID,Nemes-Nemeth Olivia²^ORCID,Ayalon Oshrat³^ORCID,Goetzen Angelica²^ORCID,Gummadi Krishna P.²^ORCID,Redmiles Elissa M.⁴^ORCID,Roesner Franziska⁵^ORCID

Affiliation:

1. TU Delft, Netherlands and Max Planck Institute for Informatics, Germany

2. Max Planck Institute for Software Systems, Germany

3. University of Haifa, Israel and Max Planck Institute for Software Systems, Germany

4. Georgetown University, USA

5. Paul G. Allen School of Computer Science & Engineering, University of Washington, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613904.3642433

Reference73 articles.

1. Jack Bandy and Nicholas Diakopoulos. 2020. #TulsaFlop: A Case Study of Algorithmically-Influenced Collective Action on TikTok. In FAccTRec.

2. A global pandemic in the time of viral memes: COVID-19 vaccine misinformation and disinformation on TikTok

3. #Climate Change on TikTok: A Content Analysis of Videos

4. BBC. 2021. TikTok named as the most downloaded app of 2020. https://www.bbc.com/news/business-58155103.

5. Matthew Bietz, Kevin Patrick, and Cinnamon Bloss. 2019. Data donation as a model for citizen science health research. Citizen Science: Theory and Practice 4, 1 (2019).

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