Pinpointing Influence in Pinterest

The success of most applications that run on top of a social network infrastructure is due to the social ties among their users; the users can get informed about the activity of their friends and acquaintances, and, hence, new ideas, habits, and products have the opportunity to gain popularity. Therefore, understanding the influence dynamics on social networks provides us with insights that are useful in designing efficient social network applications. In this work we focus on Pinterest, a social network that is often used to promote commercial products, and investigate the influence mechanisms in it. We examine the user indegree and PageRank as potential estimators of the number of repins and likes the user may receive. We observe that, although both measures are weakly associated with user influence in Pinterest, PageRank is much more powerful than indegree in revealing how much influential a user is.

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