2019
NAACL
NAACL 2019
Detecting Derogatory Compounds – An Unsupervised Approach
Abstract
AbstractWe examine the new task of detecting derogatory compounds (e.g. “curry muncher”). Derogatory compounds are much more difficult to detect than derogatory unigrams (e.g. “idiot”) since they are more sparsely represented in lexical resources previously found effective for this task (e.g. Wiktionary). We propose an unsupervised classification approach that incorporates linguistic properties of compounds. It mostly depends on a simple distributional representation. We compare our approach against previously established methods proposed for extracting derogatory unigrams.
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Keyword Pioneer
— derogatory compound
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning