Big-Five Personality Prediction Based on User Behaviors at Social Network Sites

TL;DR

This paper presents a method to predict Big-Five personality traits from social network site behaviors, demonstrating that online actions can reliably reflect underlying personality dimensions.

Contribution

It introduces a novel approach to directly predict personality traits from SNS behaviors, bridging psychological analysis with online behavior data.

Findings

Extraversion correlates with higher status republishing proportion.

Neuroticism correlates with a higher proportion of angry blogs.

Users' personalities can be predicted with reasonable accuracy from their SNS behaviors.

Abstract

Many customer services are already available at Social Network Sites (SNSs), including user recommendation and media interaction, to name a few. There are strong desires to provide online users more dedicated and personalized services that fit into individual's need, usually strongly depending on the inner personalities of the user. However, little has been done to conduct proper psychological analysis, crucial for explaining the user's outer behaviors from their inner personality. In this paper, we propose an approach that intends to facilitate this line of research by directly predicting the so called Big-Five Personality from user's SNS behaviors. Comparing to the conventional inventory-based psychological analysis, we demonstrate via experimental studies that users' personalities can be predicted with reasonable precision based on their online behaviors. Except for proving some former behavior-personality correlation results, our experiments show that extraversion is positively related to one's status republishing proportion and neuroticism is positively related to the proportion of one's angry blogs (blogs making people angry).