Content Sharing in a Social Broadcasting Environment: Evidence from Twitter

Abstract

The rise of social broadcasting technologies has greatly facilitated open access to information worldwide, not only by powering decentralized information production and consumption, but also by expediting information diffusion through social interactions like content sharing. We study users’ voluntary information sharing in the context of Twitter, the predominant social broadcasting site, by modeling both the technology and user behavior. We collect a detailed dataset about the official content-sharing function on Twitter, called retweet, and document the statistical relationships between the users’ social network characteristics and their retweeting acts. We then estimate a more structural model using conditional Maximum Likelihood Estimation (MLE) method. The empirical results convincingly support our hypothesis that weak ties are more likely to engage in the social exchange process of content sharing. Specifically, we find that after an author posts a median quality tweet (as defined in the sample), the likelihood that a unidirectional follower will retweet is 3.1% higher than the likelihood that a bidirectional follower will.

Keywords: Twitter, social networks, retweet, social broadcasting