For Whom to Tweet? Evidence from a Large-Scale Social Media Platform
48 Pages Posted: 31 May 2016 Last revised: 29 Jan 2017
Date Written: January 1, 2017
We study the effects of peer-group sizes on tweeting in a large-scale and influential social media platform. Tweets in social media disseminate information and exert social influence. However, 50% of the users post less than 6 tweets per month and contribute to less than 15% of the tweets in stock, while the top 10% post over 40 tweets a month and contribute to more than half of the tweets in stock. We attribute the highly unbalanced contribution to a user's conflicting incentives of free-riding and maximizing social influence. We exploit the asymmetry of a user's peer groups (followers and followees, groups of people following and being followed by the user) to disentangle these incentives, and devise empirical strategies to deal with the endogenous network formation. We find asymmetric effects, in both signs and sizes, of followers and followees. A larger group of followers leads a user to tweet more, while a larger group of followees leads a user to tweet less. As the follower effects are dominant, our simulations indicate that by randomly adding 1% new connections the platform could increase the total tweets by 25%. Targeting occasional tweeters is even more effective in promoting the activeness of this platform.
Keywords: Social media, Social networks, User-generated content, Peer effects, Public goods
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