Inducing a lexicon of abusive words: a feature-based approach - Wiegand, Michael; Ruppenhofer, Josef; Schmidt, Anna; Greenberg, Clayton (The 2018 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - proceedings of the conference, 2018)
We address the detection of abusive words. The task is to identify such words among a set of negative polar expressions. We propose novel features employing information from both corpora and lexical resources. These features are calibrated on a small manually annotated base lexicon which we use to produce a large lexicon. We show that the word-level information we learn cannot be equally derived from a large dataset of annotated microposts. We demonstrate the effectiveness of our (domain-independent) lexicon in the cross-domain detection of abusive microposts.
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