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...
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| Vydáno v: | Jisuanji kexue yu tansuo Ročník 15; číslo 8; s. 1459 - 1468 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | čínština |
| Vydáno: |
Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
01.08.2021
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| Témata: | |
| ISSN: | 1673-9418 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | 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 |
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| ISSN: | 1673-9418 |
| DOI: | 10.3778/j.issn.1673-9418.2007009 |