Unexpected Relevance: An Empirical Study of Serendipity in Retweets

Authors

  • Tao Sun Peking University
  • Ming Zhang Peking University
  • Qiaozhu Mei University of Michigan

DOI:

https://doi.org/10.1609/icwsm.v7i1.14435

Keywords:

Serendipity, Microblogs, Likelihood Ratio Test

Abstract

Serendipity is a beneficial discovery that happens in an unexpected way. It has been found spectacularly valuable in various contexts, including scientific discoveries, acquisition of business, and recommender systems. Although never formally proved with large-scale behavioral analysis, it is believed by scientists and practitioners that serendipity is an important factor of positive user experience and increased user engagement. In this paper, we take the initiative to study the ubiquitous occurrence of serendipitious information diffusion and its effect in the context of microblogging communities. We refer to serendipity as unexpected relevance, then propose a principled statistical method to test the unexpectedness and the relevance of information received by a microblogging user, which identifies a serendipitous diffusion of information to the user. Our findings based on large-scale behavioral analysis reveal that there is a surprisingly strong presence of serendipitous information diffusion in retweeting, which accounts for more than 25% of retweets in both Twitter and Weibo. Upon the identification of serendipity, we are able to conduct observational analysis that reveals the benefit of serendipity to microblogging users. Results show that both the discovery and provision of serendipity increase the level of user activities and social interactions, while the provision of serendipitous information also increases the influence of Twitter users.

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Published

2021-08-03

How to Cite

Sun, T., Zhang, M., & Mei, Q. (2021). Unexpected Relevance: An Empirical Study of Serendipity in Retweets. Proceedings of the International AAAI Conference on Web and Social Media, 7(1), 592-601. https://doi.org/10.1609/icwsm.v7i1.14435