Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter’s Trending Topics


  • Joseph Schlessinger U.S. Army
  • Kiran Garimella Rutgers University
  • Maurice Jakesch Cornell University
  • Dean Eckles MIT




Centrality/influence of social media publications and authors, Engagement, motivations, incentives, and gamification., Social network analysis; communities identification; expertise and authority discovery, Trend identification and tracking; time series forecasting


In addition to more personalized content feeds, some leading social media platforms give a prominent role to content that is more widely popular. On Twitter, "trending topics" identify popular topics of conversation on the platform, thereby promoting popular content which users might not have otherwise seen through their network. Hence, "trending topics" potentially play important roles in influencing the topics users engage with on a particular day. Using two carefully constructed data sets from India and Turkey, we study the effects of a hashtag appearing on the trending topics page on the number of tweets produced with that hashtag. We specifically aim to answer the question: How many new tweeting using that hashtag appear because a hashtag is labeled as trending? We distinguish the effects of the trending topics page from network exposure and find there is a statistically significant, but modest, return to a hashtag being featured on trending topics. Analysis of the types of users impacted by trending topics shows that the feature helps less popular and new users to discover and spread content outside their network, which they otherwise might not have been able to do.




How to Cite

Schlessinger, J., Garimella, K., Jakesch, M., & Eckles, D. (2023). Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter’s Trending Topics. Proceedings of the International AAAI Conference on Web and Social Media, 17(1), 777-786. https://doi.org/10.1609/icwsm.v17i1.22187