Sentiment Analysis using BERT, LSTM, and Cognitive Dictionary

Due to the epidemic situation, in order to greatly reduce the infection risk of face-to-face interviews, this paper implements the BERT combined with RCNN to judge the positive and negative directions of the text, and then uses BERT's next sentence prediction (NSP) to find out the topic-related...

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Bibliographic Details
Main Authors: Tseng, Hsiao-Ting, Zheng, You-Zhan, Hsieh, Chen-Chiung
Format: Conference Proceeding
Language:English
Subjects:
Bit error rate
Data models
Dictionaries
Epidemics
Sentiment analysis
Training
Training data
Online Access:Request full text
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Summary:Due to the epidemic situation, in order to greatly reduce the infection risk of face-to-face interviews, this paper implements the BERT combined with RCNN to judge the positive and negative directions of the text, and then uses BERT's next sentence prediction (NSP) to find out the topic-related sentences in the text. Finally, a cognitive dictionary is used to calculate the degree of agreement or disagreement, so as to obtain the degree of support of the reviewer. This paper is also useful for letting visitors or authors know what the respondents' views are.
ISSN:2575-8284
DOI:10.1109/ICCE-Taiwan55306.2022.9868974