Pinned it! A Large Scale Study of the Pinterest Network

Abstract

Pinterest is an image-based online social network, which was launched in the year 2010 and has gained a lot of traction, ever since. Within 3 years, Pinterest has attained 48.7 million unique users. This stupendous growth makes it interesting to study Pinterest, and gives rise to multiple questions about it's users, and content. We characterized Pinterest on the basis of large scale crawls of 3.3 million user profiles, and 58.8 million pins. In particular, we explored various attributes of users, pins, boards, pin sources, and user locations, in detail and performed topical analysis of user generated textual content. The characterization revealed most prominent topics among users and pins, top image sources, and geographical distribution of users on Pinterest. We then tried to predict gender of American users based on a set of profile, network, and content features, and achieved an accuracy of 73.17% with a J48 Decision Tree classifier. We then exploited the users' names by comparing them to a corpus of top male and female names in the U.S.A., and achieved an accuracy of 86.18%. To the best of our knowledge, this is the first attempt to predict gender on Pinterest.