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  4. Vol 5, Issue 4, 2024

Research on Trending Algorithms of Digital Platforms: A Case Study of Little Red Book and Instagram

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DOI: 10.23977/mediacr.2024.050409 | Downloads: 42 | Views: 721

Author(s)

Jiatong Liu 1

Affiliation(s)

1 School of Fashion Communication, Beijing Institute of Fashion Technology, Beijing, 100105, China

Corresponding Author

Jiatong Liu

ABSTRACT

In the digital age, the rapid development of digital technology has profoundly impacted the trending dissemination mechanisms of social media platforms. This paper examines the algorithmic recommendation mechanisms of trending topics on little red book and instagram, as well as their effects on user social interaction and content dissemination. The study finds that both platforms utilize aggregation algorithms to capture users' collective attention, enhancing the social interactivity and topic expansion of the platforms. However, algorithm-based personalized recommendations also lead to issues such as "information silos" and "algorithm manipulation," which hinder the free flow of information and limit users' exposure to diverse perspectives. Therefore, to balance user needs with information diversity, platforms should optimize their algorithmic recommendation mechanisms, increase content variety, and prevent the formation of information islands. Additionally, it is essential to strengthen content review and governance, improve algorithm transparency, and ensure content security and user rights on the platforms.

KEYWORDS

Trending topics; Algorithm manipulation; Information silos; little red book; Instagram

CITE THIS PAPER

Jiatong Liu, Research on Trending Algorithms of Digital Platforms: A Case Study of Little Red Book and Instagram. Media and Communication Research (2024) Vol. 5: 58-68. DOI: http://dx.doi.org/10.23977/mediacr.2024.050409.

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