Work

Incorporating Textual Information on User Behavior for Personality Prediction

Year: 2019

Type: conference-paper

Abstract: Several recent studies have shown that textual information of user posts and user behaviors such as liking and sharing the specific posts are useful for predicting the personality of social media users.However, less attention has been paid to the textual information derived from the user behaviors.In this paper, we investigate the effect of textual information on user behaviors for personality prediction.Our experiments on the personality prediction of Twitter users show that the textual information of user behaviors is more useful than the cooccurrence information of the user behaviors.They also show that taking user behaviors into account is crucial for predicting the personality of users who do not post frequently.

Source: Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW)

DOI: 10.18653/v1/p19-2024

Authors: Kosuke Yamada, Ryohei Sasano, Koichi Takeda

Institution: Nagoya University

Language: English

Topic: Authorship Attribution and Profiling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Japan Society for the Promotion of Science

Award: Acquisition of cross-word frame knowledge from large texts and its application to semantic analysis