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We propose to use abusive emojis, such as the “middle finger” or “face vomiting”, as a proxy for learning a lexicon of abusive words. Since it represents extralinguistic information, a single emoji can co-occur with different forms of explicitly abusive utterances. We show that our approach generates a lexicon that offers the same performance in cross-domain classification of abusive microposts as the most advanced lexicon induction method. Such an approach, in contrast, is dependent on manually annotated seed words and expensive lexical resources for bootstrapping (e.g. WordNet). We demonstrate that the same emojis can also be effectively used in languages other than English. Finally, we also show that emojis can be exploited for classifying mentions of ambiguous words, such as “fuck” and “bitch”, into generally abusive and just profane usages.
Emoticons erfreuen sich auf der ganzen Welt großer Beliebtheit, vor allem in der alltäglichen elektronischen Kommunikation wie E-Mail, SMS, Forumsdiskussionen, Instant Messaging, Facebook oder Twitter. Zum ersten Mal in der Geschichte wurde 2015 von den Sprachbeobachtern der britischen Oxford Dictionaries ein Emoticon zum Wort des Jahres gewählt: das Grinsegesicht, dem die Freudentränen aus den Augen spritzen (vgl.<www.sueddeutsche.de/kultur/britisches-wortdes-jahres-was-haben wir-gelacht-1.2740952>, Stand: 8.11.2017). Die Jury begründete ihre Wahl wie folgt: „[E]moji have come to embody a core aspect of living in a digital world that is visually driven, emotionally expressive, and obsessively immediate.“