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ALW1: 1st Workshop on Abusive Language Online to be held at the annual meeting of the Association of Computational Linguistics (ACL) 2017 (Vancouver, Canada), August 3rd or 4th, 2017.


Important dates

Submission due: April 27th

Author Notification: May 17th

Camera Ready: May 26th

Workshop Date: August 3rd or 4th


Overview


The last few years have seen a surge in abusive online behavior, with governments, social media platforms, and individuals struggling to cope with the consequences. Online forums, comment sections, and social media interaction in general have become a playground of bullying, scapegoating, and hate speech. These forms of online aggression not only poison the social climate of the communities that experience it, but also lower the inhibition for direct physical violence, and increasingly even result in it.


As a field that directly works with computing over language, Natural Language Processing researchers are in a unique position to develop automated methods to analyse, detect, and filter abusive language. Additionally, we recognize that addressing abusive language is not solely the purview of NLP approaches but is a truly multi-disciplinary problem and thus requires knowledge from other fields, including but not limited to: psychology, sociology, law, gender studies, digital communication, and critical race theory.


In this one day workshop, we aim to provide a space for researchers of various disciplines to meet and discuss approaches to abusive language. The workshop will include invited speakers and panelists from fields outside of NLP, as well as solicit papers from researchers across all areas.  In addition, the workshop will host an “unshared task”.


Paper Topics


We invite long and short papers on any of the following general topics:

  • NLP models and methods for abusive language detection

  • Application of NLP tools to analyze social media content and other large data sets

  • NLP models for cross-lingual abusive language detection

  • The social and personal consequences of being the target of abusive language and targeting others with abusive language

  • Assessment of current non-NLP methods of addressing abusive language

  • Legal ramifications of measures taken against abusive language use

  • Best practices for using NLP techniques in watchdog settings

  • Development of corpora and annotation guidelines


Panel Discussion Topics


Potential panel discussion topics reflect the relevance for industry and individuals:

  • Responsibility of companies and governments in monitoring speech

  • Privacy and ethical implications of abusive language detection (false positives)

  • Follow-up: what to do when a community experiences abusive language

  • Personal experiences from individuals who have been threatened online

  • Best methods for cross-pollination of ideas between fields


Unshared Task

In order to encourage focused contributions, we direct researchers to consider the following list of data sets an unshared task, where participants can choose from a list of datasets to conduct their experiments. This list includes:

  • English Twitter Data Set [Waseem and Hovy, NAACL 2016]

  • German Twitter Data Set [Ross et al. NLP4CMC 2016]

  • Wikipedia Abusive Language Data Set [Wulczyn et al., Preprint available here]


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