Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Identity construction on Facebook: Digital empowerment in anchored relationships
Computers in Human Behavior
Personality and motivations associated with Facebook use
Computers in Human Behavior
Who interacts on the Web?: The intersection of users' personality and social media use
Computers in Human Behavior
Social network use and personality
Computers in Human Behavior
Predicting personality with social media
CHI '11 Extended Abstracts on Human Factors in Computing Systems
Inferring the demographics of search users: social data meets search queries
Proceedings of the 22nd international conference on World Wide Web
Predicting user personality by mining social interactions in Facebook
Journal of Computer and System Sciences
How do people compare themselves with others on social network sites?: The case of Facebook
Computers in Human Behavior
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We show how users' activity on Facebook relates to their personality, as measured by the standard Five Factor Model. Our dataset consists of the personality profiles and Facebook profile data of 180,000 users. We examine correlations between users' personality and the properties of their Facebook profiles such as the size and density of their friendship network, number uploaded photos, number of events attended, number of group memberships, and number of times user has been tagged in photos. Our results show significant relationships between personality traits and various features of Facebook profiles. We then show how multivariate regression allows prediction of the personality traits of an individual user given their Facebook profile. The best accuracy of such predictions is achieved for Extraversion and Neuroticism, the lowest accuracy is obtained for Agreeableness, with Openness and Conscientiousness lying in the middle.