For this sixth edition of the Workshop on Online Abuse and Harms (6th WOAH!) we advance research in online abuse through our theme: On Developing Resources and Technologies for low resource Online Abuse and Harms. We continue to emphasize the need for inter-, cross- and anti- disciplinary work on online abuse and harms, and invite paper submissions from a range of fields. These include but are not limited to: NLP, machine learning, computational social sciences, law, politics, psychology, network analysis, sociology and cultural studies. Continuing the tradition started in WOAH 4, we invite civil society, in particular individuals and organisations working with women and marginalised communities who are often disproportionately affected by online abuse, to submit reports, case studies, findings, data, and to record their lived experiences. We hope that through these engagements WOAH can directly address the issues faced by those on the front-lines of tackling online abuse.
Authors are invited to submit full papers of up to 8 pages of content and short papers of up to 4 pages of content, with unlimited pages for references. Accepted papers will be given an additional page of content to address reviewer comments. Previously published papers cannot be accepted. Papers that are currently undergoing review at other venues are welcome.
Topics related to developing computational models and systems include but are not limited to:
NLP and Computer Vision models and methods for detecting abusive language online, including, but not limited to hate speech, gender-based violence, cyberbullying etc.
Application of NLP and Computer Vision tools to analyze social media content and other large data sets
NLP and Computer Vision models for cross-lingual abusive language detection
Computational models for multi-modal abuse detection
Development of corpora and annotation guidelines
Critical algorithm studies with a focus on content moderation technology
Human-Computer Interaction for abusive language detection systems
Best practises for using NLP and Computer Vision techniques in watchdog settings
Submissions addressing interpretability and social biases in content moderation technologies
Topics related to legal, social, and policy considerations of abusive language online include but are not limited to:
The social and personal consequences of being the target of abusive language and targeting others with abusive language
Assessment of current (computational and non-computational) methods of addressing abusive language
Legal ramifications of measures taken against abusive language use
Social implications of monitoring and moderating unacceptable content
Considerations of implemented and proposed policies for dealing with abusive language online and the technological means of dealing with it.
We particularly invite contributions on the stated areas that address these topics in low resource settings.
We welcome non-archival submissions (2 pages + 2 pages for references), which can include work previously published elsewhere.
We invite reports from civil society. These are non-archival submissions, and can include previously published work. They must be a minimum of two pages, with no upper limit. Please contact us if you have any queries about the civil society reports.
Submission link: https://www.softconf.com/naacl2022/WOAH2022/
Submission deadline: Apr 18, 2022 Extended!
Notification date: May 9, 2022
Camera-ready date: May 23, 2022
Workshop: July 14, 2022 at NAACL
We use the ACL Rolling Review Submission Guidelines for submissions. We have also included conflict of interest in the submission form. You should mark all potential reviewers who have been authors on the paper, are from the same research group or institution, or who have seen versions of this paper or discussed it with you.
We request that all papers adhere to our submission policies. Submissions will be reviewed by the program committee. As reviewing is anonymised, please ensure that papers are anonymous. Self-references that reveal the author's identity, e.g., "We previously showed (Smith, 1991) ...", should be avoided. Instead, use citations such as "Smith previously showed (Smith, 1991) ...".
Digital technologies have brought myriad benefits for society, transforming how people connect, communicate and interact with each other. However, they have also enabled harmful and abusive behaviours to reach large audiences and for their negative effects to be amplified, including interpersonal aggression, bullying and hate speech. Work on online abuse and harms has traditionally centred on abuse in English and other Western European languages, further widening the resource gap between Western European languages and all other languages.
As academics, civil society, policymakers and tech companies devote more resources and effort to tackling online abuse, there is a pressing need for scientific research that critically and rigorously investigates how it is defined, detected and countered. Technical disciplines such as machine learning (ML), natural language processing (NLP) and statistics have made substantial advances in this field. However, concerns have been raised about the differences in attention given to different languages and geographies. For example, English, particularly dominant forms of American English, are overrepresented in most NLP resources. Technological solutions can be developed for speakers of other dialects and languages. On the other hand, languages such as Yuruba, Urdu, Amharic, and many other languages have few to no resources available, thus providing significant challenges in developing technological systems for the detection of abuse and other harms.