A weakly-supervised graph-based joint sentiment topic model for multi-topic sentiment analysis

Tao Zhou; Kris M. Y. Law; Douglas Creighton

doi:10.1016/j.ins.2022.07.126

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JOURNAL ARTICLE

A weakly-supervised graph-based joint sentiment topic model for multi-topic sentiment analysis

Tao Zhou Kris M. Y. Law Douglas Creighton

Year: 2022 Journal: Information Sciences Vol: 609 Pages: 1030-1051 Publisher: Elsevier BV

DOI: 10.1016/j.ins.2022.07.126

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Keywords:

Sentiment analysis Computer science Graph Joint (building) Artificial intelligence Natural language processing Machine learning Information retrieval Data mining Theoretical computer science

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3.13

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0.89

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Topics

Sentiment Analysis and Opinion Mining

Physical Sciences → Computer Science → Artificial Intelligence

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

A weakly-supervised graph-based joint sentiment topic model for multi-topic sentiment analysis

Metrics

Citation History

Topics

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