Prestige bias drives the viral spread of content reposted by influencers in online communities

2024-11-08

AI Summary

This study investigates whether reputation bias—i.e., whether posts from high-influence users significantly enhance information diffusion—exists in online communities. Leveraging a large-scale empirical analysis of 55 million tweets and 520 million retweets, we quantify user influence using the *hg*-score, construct temporal cascade models, and conduct multiple robustness checks. Our key contributions are: (1) users in the top 0.1% by *hg*-score drive nearly 50% of all retweet cascades; (2) cascades involving such high-*hg* users exhibit significantly broader reach, longer duration, and higher per-step retweet probability; and (3) this reputational advantage intensifies during viral diffusion. These findings provide rigorous evidence for systematic reputation bias in digital societies, revealing the structural dominance of a small set of high-reputation nodes in shaping global information diffusion patterns.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Web Mining and Content Analysis: Content-based information diffusion
• User Modeling, Personalization and Recommendation: Social recommender systems and personalization for the social Web

Abstract

Cultural evolution theory suggests that prestige bias - whereby individuals preferentially learn from prestigious figures - has played a key role in human ecological success. However, its impact within online environments remains unclear, particularly with respect to whether reposts by prestigious individuals amplify diffusion more effectively than reposts by noninfluential users. We analyzed over 55 million posts and 520 million reposts on Twitter (currently X) to examine whether users with high influence scores (hg indices) more effectively amplified the reach of others' content. Our findings indicate that posts shared by influencers are more likely to be further shared than those shared by non-influencers. This effect persisted over time, especially in viral posts. Moreover, a small group of highly influential users accounted for approximately half of the information flow within repost cascades. These findings demonstrate a prestige bias in information diffusion within the digital society, suggesting that cognitive biases shape content spread through reposting.

Problem

• Examines prestige bias in online content diffusion
• Assesses influencer impact on content reach and sharing
• Analyzes role of cognitive biases in digital information spread

Innovation

• Analyzed 55M posts and 520M reposts on Twitter
• Examined influencer impact using hg indices
• Identified prestige bias in digital information diffusion