Study on Predicting Psychological Traits of Online Text by BERT

With the rapid development and popularity of the Internet, an increasing number of people would like to use online platforms to express themselves and communicate with others. It is inevitable that a large number of online text data are constantly emerging with personal information, which often indi...

Full description

Saved in:
Bibliographic Details
Published in:Jisuanji kexue yu tansuo Vol. 15; no. 8; pp. 1459 - 1468
Main Author: ZHANG Han, JIA Tianyuan, LUO Fang, ZHANG Sheng, WU Xia
Format: Journal Article
Language:Chinese
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 01.08.2021
Subjects:
ISSN:1673-9418
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the rapid development and popularity of the Internet, an increasing number of people would like to use online platforms to express themselves and communicate with others. It is inevitable that a large number of online text data are constantly emerging with personal information, which often indicate individual real expression in different conditions and reflect personal inner psychological traits and personality tendency. Applying text mining techniques to analyzing psychological traits behind the online text is not only helpful for individuals to understand themselves, but also useful to avoid the motivation interfere while using traditional methods for psychological assessment. In recent years, the language model named bidirectional encoder representations from transformers (BERT) has greatly improved the performance of both the text classification task and the sentiment analysis task. In this paper, prediction models for psychological traits are constructed based on online text. Comprehensive semantic
ISSN:1673-9418
DOI:10.3778/j.issn.1673-9418.2007009