2017
EMNLP
EMNLP 2017
Topic-Based Agreement and Disagreement in US Electoral Manifestos
Abstract
AbstractWe present a topic-based analysis of agreement and disagreement in political manifestos, which relies on a new method for topic detection based on key concept clustering. Our approach outperforms both standard techniques like LDA and a state-of-the-art graph-based method, and provides promising initial results for this new task in computational social science.
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Interdisciplinary Bridge
— Data Science & Analytics and Machine Learning and Natural Language Processing
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Keyword Pioneer
— computational social science
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Hot Topic Early Bird
— text analysis
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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