Examining the Impact of User Interaction Behavior on the Effectiveness of Social Media Content Recommendation

DOI

10.2991/978-2-38476-577-5_76How to use a DOI?

Keywords

User interaction behavior; Social media; Filter bubble; Content recommendation; Social network heterogeneity

Abstract

The widespread use of social media platforms has significantly transformed the way people access information. However, social platform’s recommendation algorithm influences this progress, which largely determines content available to users. This process can lead to the ‘filter bubble’ effect, limiting user from being exposed to different perspectives. This study investigates the bidirectional interaction between user’s interaction behavior and recommendation mechanism. It focuses on how user’s positive interaction (like, collect, share) and negative interaction (using ‘uninterested’ function) influence content filtering. A questionnaire survey was conducted to collect data on the frequency of different interaction behaviors (independent variable), perceived content recommendations (dependent variable) and social network heterogeneity (moderator variable). By conducting correlation analysis of the variables, the study confirmed the research hypothesis that positive interaction behavior increased recommendations of homogeneous content, whereas negative interactions reduced similar content recommendations. User’s social network heterogeneity influences this process by negatively reduce positive interaction behavior’s impact on homogeneous content recommendation. These findings indicate that more active user actions are required to shape better online environment.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rui Chen
PY  - 2026
DA  - 2026/05/15
TI  - Examining the Impact of User Interaction Behavior on the Effectiveness of Social Media Content Recommendation
BT  - Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
PB  - Atlantis Press
SP  - 731
EP  - 739
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-577-5_76
DO  - 10.2991/978-2-38476-577-5_76
ID  - Chen2026
ER  -