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Gender bias in sentiment analysis
Thelwall, Mike
Thelwall, Mike
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2018-02-14
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Abstract
Purpose: To test if there are biases in lexical sentiment analysis accuracy between reviews authored by males and females. Design: This paper uses datasets of TripAdvisor reviews of hotels and restaurants in the UK written by UK residents to contrast the accuracy of lexical sentiment analysis for males and females. Findings: Male sentiment is harder to detect because it is less explicit. There was no evidence that this problem could be solved by gender-specific lexical sentiment analysis. Research limitations: Only one lexical sentiment analysis algorithm was used. Practical implications: Care should be taken when drawing conclusions about gender differences from automatic sentiment analysis results. When comparing opinions for product aspects that appeal differently to men and women, female sentiments are likely to be overrepresented, biasing the results. Originality/value: This is the first evidence that lexical sentiment analysis is less able to detect the opinions of one gender than another.
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Thelwall, M. (2018), "Gender bias in sentiment analysis", Online Information Review, 42 (1), pp. 45-57. doi: 10.1108/OIR-05-2017-0139
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Journal article
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en
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This is an accepted manuscript of an article published by Emerald Publishing Limited in Online Information Review on 14/02/2018, available online: https://doi.org/10.1108/OIR-05-2017-0139
The accepted version of the publication may differ from the final published version.
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1468-4527