2018
NAACL
NAACL 2018
Understanding the Effect of Gender and Stance in Opinion Expression in Debates on “Abortion”
Abstract
AbstractIn this paper, we focus on understanding linguistic differences across groups with different self-identified gender and stance in expressing opinions about ABORTION. We provide a new dataset consisting of users’ gender, stance on ABORTION as well as the debates in ABORTION drawn from debate.org. We use the gender and stance information to identify significant linguistic differences across individuals with different gender and stance. We show the importance of considering the stance information along with the gender since we observe significant linguistic differences across individuals with different stance even within the same gender group.
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Interdisciplinary Bridge
— Interdisciplinary and Natural Language Processing
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Keyword Pioneer
— opinion expression
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Hot Topic Early Bird
— opinion mining
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio