Machine Learning Department
School of Computer Science, Carnegie Mellon University


Understanding the Interaction between Interests,
Conversations and Friendships in Facebook

Qirong Ho, Rong Yan*, Rajat Raina*, Eric P. Xing

November 2012


Keywords: Facebook data, user interest visualization, multi-view model, topic model, network model

In this paper, we explore salient questions about user interests, conversations and friendships in the Facebook social network, using a novel latent space model that integrates several data types. A key challenge of studying Facebook's data is the wide range of data modalities such as text, network links, and categorical labels. Our latent space model seamlessly combines all three data modalities over millions of users, allowing us to study the interplay between user friendships, interests, and higher-order network-wide social trends on Facebook. The recovered insights not only answer our initial questions, but also reveal surprising facts about user interests in the context of Facebook's ecosystem. We also confirm that our results are significant with respect to evidential information from the study subjects.

25 pages

*Facebook, 10 Hacker Way, Menlo Park CA 94025

SCS Technical Report Collection
School of Computer Science