research-article

A Measurement Study of Hate Speech in Social Media

Authors:

Mainack Mondal,

Leandro Araújo Silva,

Fabrício BenevenutoAuthors Info & Claims

HT '17: Proceedings of the 28th ACM Conference on Hypertext and Social Media

Pages 85 - 94

https://doi.org/10.1145/3078714.3078723

Published: 04 July 2017 Publication History

Abstract

Social media platforms provide an inexpensive communication medium that allows anyone to quickly reach millions of users. Consequently, in these platforms anyone can publish content and anyone interested in the content can obtain it, representing a transformative revolution in our society. However, this same potential of social media systems brings together an important challenge---these systems provide space for discourses that are harmful to certain groups of people. This challenge manifests itself with a number of variations, including bullying, offensive content, and hate speech. Specifically, authorities of many countries today are rapidly recognizing hate speech as a serious problem, specially because it is hard to create barriers on the Internet to prevent the dissemination of hate across countries or minorities. In this paper, we provide the first of a kind systematic large scale measurement and analysis study of hate speech in online social media. We aim to understand the abundance of hate speech in online social media, the most common hate expressions, the effect of anonymity on hate speech and the most hated groups across regions. In order to achieve our objectives, we gather traces from two social media systems: Whisper and Twitter. We then develop and validate a methodology to identify hate speech on both of these systems. Our results identify hate speech forms and unveil a set of important patterns, providing not only a broader understanding of online hate speech, but also offering directions for detection and prevention approaches.

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Cited By

Lei WAbdullah NSyed Aris S(2024)A Systematic Literature Review on Automatic Sexism Detection in Social MediaEngineering, Technology & Applied Science Research10.48084/etasr.888114:6(18178-18188)Online publication date: 2-Dec-2024
https://doi.org/10.48084/etasr.8881
Ojha NVaish A(2024)Hate Speech in Indian Cyber Space at the Intersection of Law and TechnologyIntersections Between Rights and Technology10.4018/979-8-3693-1127-1.ch009(156-191)Online publication date: 10-Jul-2024
https://doi.org/10.4018/979-8-3693-1127-1.ch009
Beer CManiora JPott C(2024)The Risk of Silence—How the Capital Market Penalizes Social Media PassivityJournal of Information Systems10.2308/ISYS-2023-05938:1(5-38)Online publication date: 20-Feb-2024
https://doi.org/10.2308/ISYS-2023-059
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Index Terms

A Measurement Study of Hate Speech in Social Media
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
2. Information systems
  1. World Wide Web
    1. Web applications
      1. Social networks

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Published In

cover image ACM Conferences

HT '17: Proceedings of the 28th ACM Conference on Hypertext and Social Media

July 2017

336 pages

ISBN:9781450347082

DOI:10.1145/3078714

General Chairs:
Peter Dolog
Aalborg University, Denmark
,
Peter Vojtas
Charles University, Prague, Czech Republic
,
Program Chairs:
Francesco Bonchi
ISI Foundation, Turin, Italy
,
Denis Helic
Graz University of Technology, Austria

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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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: 04 July 2017

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HT'17: 28th Conference on Hypertext and Social Media

July 4 - 7, 2017

Prague, Czech Republic

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HT '17 Paper Acceptance Rate 19 of 69 submissions, 28%;

Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

Lei WAbdullah NSyed Aris S(2024)A Systematic Literature Review on Automatic Sexism Detection in Social MediaEngineering, Technology & Applied Science Research10.48084/etasr.888114:6(18178-18188)Online publication date: 2-Dec-2024
https://doi.org/10.48084/etasr.8881
Ojha NVaish A(2024)Hate Speech in Indian Cyber Space at the Intersection of Law and TechnologyIntersections Between Rights and Technology10.4018/979-8-3693-1127-1.ch009(156-191)Online publication date: 10-Jul-2024
https://doi.org/10.4018/979-8-3693-1127-1.ch009
Beer CManiora JPott C(2024)The Risk of Silence—How the Capital Market Penalizes Social Media PassivityJournal of Information Systems10.2308/ISYS-2023-05938:1(5-38)Online publication date: 20-Feb-2024
https://doi.org/10.2308/ISYS-2023-059
Alhazmi AMahmud RIdris NMohamed Abo MEke C(2024)Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning modelsPLOS ONE10.1371/journal.pone.030565719:7(e0305657)Online publication date: 17-Jul-2024
https://doi.org/10.1371/journal.pone.0305657
Mozafari MMnassri KFarahbakhsh RCrespi N(2024)Offensive language detection in low resource languages: A use case of Persian languagePLOS ONE10.1371/journal.pone.030416619:6(e0304166)Online publication date: 21-Jun-2024
https://doi.org/10.1371/journal.pone.0304166
Mansur ZOmar NTiun SAlshari E(2024)A normalization model for repeated letters in social media hate speech text based on rules and spelling correctionPLOS ONE10.1371/journal.pone.029965219:3(e0299652)Online publication date: 21-Mar-2024
https://doi.org/10.1371/journal.pone.0299652
Jaron Bedrosova MDufkova EMachackova HHuang YBlaya C(2024)Bias-Based Cyberaggression Related To Origin, Religion, Sexual Orientation, Gender, and Weight: Systematic Review of Young People’s Experiences, Risk and Protective Factors, and the ConsequencesTrauma, Violence, & Abuse10.1177/1524838024127597126:1(86-102)Online publication date: 8-Sep-2024
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Becker M(2024)IntroductionAntisemitism in Online Communication10.11647/obp.0406.00(1-18)Online publication date: 21-Jun-2024
https://doi.org/10.11647/obp.0406.00
Kaur MSaini M(2024)Artificial Intelligence inspired method for cross-lingual cyberhate detection from low resource languagesACM Transactions on Asian and Low-Resource Language Information Processing10.1145/367717623:9(1-23)Online publication date: 11-Jul-2024
https://dl.acm.org/doi/10.1145/3677176
Gao ZThebault-Spieker J(2024)Investigating Influential Users' Responses to Permanent Suspension on Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/36373568:CSCW1(1-41)Online publication date: 26-Apr-2024
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