Recognizing Stances in Ideological On-Line Debates
作者： Swapna Somasundaran , Janyce Wiebe
DOI:
关键词: Epistemology 、 Line (text file) 、 Ideology 、 Construct (philosophy) 、 Order (exchange) 、 Lexicon 、 Baseline (configuration management) 、 Artificial intelligence 、 Stance detection 、 Computer science
摘要: This work explores the utility of sentiment and arguing opinions for classifying stances in ideological debates. In order to capture stance taking, we construct an lexicon automatically from a manually annotated corpus. We build supervised systems employing their targets as features. Our perform substantially better than distribution-based baseline. Additionally, by both types opinion features, are able unigram-based system.
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acm.org 参考文章(24)
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