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extended-abstract

Understanding Abusive Behaviour Between Online and Offline Group Discussions

Authors:

Abdulwhab Alkharashi,

Andrew Hoskins,

Catherine HapperAuthors Info & Claims

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: CS15, Pages 1 - 8

https://doi.org/10.1145/3290607.3299042

Published: 02 May 2019 Publication History

Abstract

Online discussion platforms can face multiple challenges of abusive behaviour. In order to understand the reasons for persisting such behaviour, we need to understand how users behave inside and outside a community. In this paper, we propose a novel methodology to generate a dataset from offline and online group discussion conversations. We advocate an empirical-based approach to explore the space of abusive behaviour. We conducted a user-study (N = 15) to understand what factors facilitate or amplify forms of behaviour in cases of online conversation that are less likely to be tolerated in face-to-face. The preliminary analysis validates our approach to analyse large-scale conversation dataset.

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Cited By

Brar GSharma GSingh PGupta NKalra NParashar A(2022)NOMA—Non-offensive Messaging Application Framework Using Machine Learning Technique for Online Communication Through Social MediaHuman-Centric Smart Computing10.1007/978-981-19-5403-0_27(315-328)Online publication date: 29-Nov-2022
https://doi.org/10.1007/978-981-19-5403-0_27
Sharma GBrar GSingh PGupta NKalra NParashar A(2022)An Exploration of Machine Learning and Deep Learning Techniques for Offensive Text Detection in Social Media—A Systematic ReviewInternational Conference on Innovative Computing and Communications10.1007/978-981-19-3679-1_45(541-559)Online publication date: 8-Nov-2022
https://doi.org/10.1007/978-981-19-3679-1_45

Index Terms

Understanding Abusive Behaviour Between Online and Offline Group Discussions
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing
2. Security and privacy
  1. Human and societal aspects of security and privacy
    1. Social aspects of security and privacy

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Published In

cover image ACM Conferences

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

3673 pages

ISBN:9781450359719

DOI:10.1145/3290607

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 02 May 2019

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Extended-abstract

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CHI '19

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CHI '19: CHI Conference on Human Factors in Computing Systems

May 4 - 9, 2019

Glasgow, Scotland Uk

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Cited By

Brar GSharma GSingh PGupta NKalra NParashar A(2022)NOMA—Non-offensive Messaging Application Framework Using Machine Learning Technique for Online Communication Through Social MediaHuman-Centric Smart Computing10.1007/978-981-19-5403-0_27(315-328)Online publication date: 29-Nov-2022
https://doi.org/10.1007/978-981-19-5403-0_27
Sharma GBrar GSingh PGupta NKalra NParashar A(2022)An Exploration of Machine Learning and Deep Learning Techniques for Offensive Text Detection in Social Media—A Systematic ReviewInternational Conference on Innovative Computing and Communications10.1007/978-981-19-3679-1_45(541-559)Online publication date: 8-Nov-2022
https://doi.org/10.1007/978-981-19-3679-1_45

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