This research paper investigates the impact of influencers' reposts on information diffusion within online communities, specifically on Twitter. The study analyzes a dataset of over 55 million posts and 520 million reposts to examine whether users with high influence scores (hg-index), indicative of their ability to consistently generate and spread original content, can also amplify the reach of others' content through reposts.
Research Objective:
The study aims to determine if a "prestige bias," where individuals preferentially learn from and share content from prestigious figures, exists in online environments like Twitter.
Methodology:
The researchers collected one month of Japanese-language posts and their associated follower-followee relationships from Twitter. They employed the hg-index to categorize users into six influence categories. To track information flow, they introduced the concepts of "repost cascade," "primary spread" (diffusion of original content), and "secondary spread" (diffusion of reposts). They also developed the "cascading repost probability" (CRP) to measure the efficiency of information spread through reposts.
Key Findings:
Main Conclusions:
The findings provide strong evidence for the existence of prestige bias in online information diffusion, suggesting that users are more likely to share content reposted by influential users. This cognitive bias significantly shapes content spread through reposting.
Significance:
The study highlights the crucial role of influencers in shaping online discourse and the importance of understanding prestige bias in managing information diffusion and combating misinformation online.
Limitations and Future Research:
The study focused on simple reposts and excluded quote posts, which could be explored in future research. Further investigation into the interplay between content characteristics and influencer status in shaping prestige bias is also warranted.
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by Niitsuma Tak... om arxiv.org 11-11-2024
https://arxiv.org/pdf/2411.05448.pdfDiepere vragen