Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression
Terra Blevins, Robert Kwiatkowski, Jamie MacBeth, Kathleen McKeown, Desmond Patton, Owen Rambow
Abstract
Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used and a classifier for identifying tweets that express grieving and aggression.- Anthology ID:
- C16-1207
- Volume:
- Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Yuji Matsumoto, Rashmi Prasad
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 2196–2206
- Language:
- URL:
- https://aclanthology.org/C16-1207
- DOI:
- Cite (ACL):
- Terra Blevins, Robert Kwiatkowski, Jamie MacBeth, Kathleen McKeown, Desmond Patton, and Owen Rambow. 2016. Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2196–2206, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression (Blevins et al., COLING 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/C16-1207.pdf