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As the third-largest English-language social network behind Facebook and Twitter, Pinterest has surpassed Reddit, Digg, and others to become the world’s most popular social curation site. Despite the popularity of Pinterest, there has been little scientific work examining the strategies of successful Pinterest users. We have been studying Pinterest for the past year and a half, with one paper appearing in CHI 2013 and another one to be presented at CSCW 2014. This post summarizes the highlights of the CSCW paper.

In this work we studied the types of content and behavior that attract attention — namely repins and follows — in Pinterest. We looked at a number of factors, including the diversity of pinned content, homophily (the tendency for similar people to have more social connections), and gender.

Using our dataset of thousands of Pinterest users and millions of pins, we identified a number of factors that correlated with the number of followers a user had: the most powerful correlates were obvious factors like the amount of content the user pinned and the number of other users the user followed. However, topical diversity also played a role:  the more topically diverse one’s set of pins, the more followers one tends to have, but only up to a certain point. So, in other words, the Pinterest user who pins content in many categories – e.g. food/drink, DIY, home decor, travel, etc. – tends to have more followers than the Pinterest user who sticks to a single or small number of categories. However, when the diversity of categories gets too great, the number of followers tends to go down. The figure below shows this relationship in more detail.

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This post describes work appearing at CSCW 2014.

Many online activities today involve interacting with other people, and these interactions are often dictated by social norms – unspoken rules that classify socially acceptable behavior.  Whether intentional or otherwise, people sometimes break these rules.  Behavior that goes against established norms is called deviant behavior, and in many cases is assumed to be negative. In online communities, deviant behavior is commonly believed to be harmful, and is expected to drive users to leave the community. For example, intentionally incorrect responses on a question and answer site may discourage new users from asking questions. Our work looks at patterns of player behavior in an online game where people will play bingo for money. We build a metric to predict a specific kind of deviant behavior, toxicity, and we use this metric to examine whether deviant behavior causes other players to quit.

We look at deviant behavior in the popular online game League of Legends.  League of Legends is a competitive multiplayer game where two teams of five players compete to destroy the other team’s base. Each player controls a single character, and every character has unique abilities which, when used skillfully, can help the player’s team overcome an enemy team. If you’ve never played League of Legends, check out this four-minute introduction video from League’s developer, Riot Games.

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