Publication: Replicable semi-supervised approaches to state-of-the-art stance detection of tweets
Replicable semi-supervised approaches to state-of-the-art stance detection of tweets
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Reveilhac, M., & Schneider, G. (2023). Replicable semi-supervised approaches to state-of-the-art stance detection of tweets. Information Processing & Management, 60, 103199. https://doi.org/10.1016/j.ipm.2022.103199
Abstract
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Abstract
Stance is defined as the expression of a speaker’s standpoint towards a given target or entity. To date, the most reliable method for measuring stance is opinion surveys. However, people’s increased reliance on social media makes these online platforms an essential source of comple- mentary information about public opinion. Our study contributes to the discussion surrounding replicable methods through which to conduct reliable stance detection by establishing a rule- based model, which we replicated for several targets independently.
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- Reveilhac, Maud
- Schneider, Gerold
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Reveilhac, M., & Schneider, G. (2023). Replicable semi-supervised approaches to state-of-the-art stance detection of tweets. Information Processing & Management, 60, 103199. https://doi.org/10.1016/j.ipm.2022.103199
