Users Joining Multiple Sites: Distributions and Patterns

The rise of social media has led to an explosion in the number of possible sites users can join. However, this same profusion of social media sites has made it nearly impossible for users to actively engage in all of them simultaneously. Accordingly, users must make choices about which sites to use or to neglect. In this paper, we study users that have joined multiple sites. We study how individuals are distributed across sites, the way they select sites to join, and behavioral patterns they exhibit while selecting sites. Our study demonstrates that while users have a tendency to join the most popular or trendiest sites, this does not fully explain users’ selections. We demonstrate that peer pressure also influences the decisions users make about joining emerging sites. Our life in social media is no longer limited to a single site. We post on Reddit, like on Facebook, tweet on Twitter, watch on YouTube, listen on Pandora, along with many other activities exhibited by social media users. With the constant rise of new sites and advancement of communication technology, thousands of social media sites are at our fingertips. With so many choices, our attention spans are decreasing rapidly. On average, a user spends less than a minute on an average site (BBC News 2002). With our limited time and short attention span, we often face a dilemma of choosing a handful of sites over others. How do we select these sites? As social media consumers, we are constantly seeking sites that can keep our attentions glued to our screens by providing engaging content, especially content generated by our friends. It is well-known that the likelihood of engaging in an activity is increased as more friends become engaged in that activity (Backstrom et al. 2006). Thus, it is natural to assume that users select sites where they find more friends on. On average, sites with more members are expected to contain more friends for an average individual; hence, it is expected for the users’ site selection to be statistically biased toward more popular sites. In this paper, we analyze users joining multiple sites. We show how users are dispersed across sites. By studying users across sites, we show that while there is a tendency to join popular sites, users exhibit a variety of site selection patterns. Finally, we evaluate the obtained users’ site selection patterns with an application that recommends new sites to Copyright c © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. users for joining. Our evaluation demonstrates promising results and reveals additional interesting user joining patterns. We first detail the data collection for our research. Next, we analyze user distribution across sites. Then, we outline membership patterns across sites, followed by our evaluation of these patterns. Finally, we conclude this work with a brief literature review and future directions.