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Automated Measures of Sentiment via Transformer- and Lexicon-Based Sentiment Analysis (TLSA)
  • Xinyan Zhao ,
  • Chau-Wai Wong
Xinyan Zhao
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Chau-Wai Wong
North Carolina State University, North Carolina State University

Corresponding Author:[email protected]

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The last decade witnessed the proliferation of automated content analysis in communication research. However, existing computational tools have been taken up unevenly, with powerful deep learning algorithms such as transformers rarely applied as compared to lexicon-based dictionaries. To enable social scientists to adopt modern computational methods for valid and reliable sentiment analysis of English text, we propose an open and free web service named transformer- and lexicon-based sentiment analysis (TLSA). TLSA integrates diverse tools and offers validation metrics, empowering users with limited computational knowledge and resources to reap the benefit of state-of-the-art computational methods. Two cases demonstrate the functionality and usability of TLSA. The performance of different tools varied to a large extent based on the dataset, supporting the importance of validating various sentiment tools in a specific context.
21 Nov 2023Published in Journal of Computational Social Science. 10.1007/s42001-023-00233-8