Modeling of User Portrait Through Social Media

TL;DR

This paper presents a novel computational linguistic approach to model and analyze users' personality traits and social behaviors on Sina Weibo, enabling better personalized services without disrupting users.

Contribution

It introduces the first method to link social media profile data, social behaviors, and Big Five personality traits on Sina Weibo using linguistic features.

Findings

Effective modeling of user personality traits from social media data

Correlation between social behaviors and personality traits

Potential for personalized service enhancement

Abstract

Nowadays, massive useful data of user information and social behavior have been accumulated on the Internet, providing a possibility of profiling user's personality traits online. In this paper, we propose a psychological modeling method based on computational linguistic features to profile Big Five personality traits of users on Sina Weibo (a Twitter-like microblogging service in China) and their correlations with user's social behaviors. To the best of our knowledge, this is the first research on investigating the potential relationship between profile information, social-network behaviors and personality traits of users on Sina Weibo. Our results demonstrate an effective modeling approach to understanding demographic and psychological portraits of users on social media without customer disruption, which is useful for commercial incorporations to provide better personalized products and services.