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Deep Learning for Hate Speech Detection in Tweets

Authors:

Pinkesh Badjatiya,

Shashank Gupta,

Manish Gupta,

Vasudeva VarmaAuthors Info & Claims

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

Pages 759 - 760

https://doi.org/10.1145/3041021.3054223

Published: 03 April 2017 Publication History

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Abstract

Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist, sexist or neither. The complexity of the natural language constructs makes this task very challenging. We perform extensive experiments with multiple deep learning architectures to learn semantic word embeddings to handle this complexity. Our experiments on a benchmark dataset of 16K annotated tweets show that such deep learning methods outperform state-of-the-art char/word n-gram methods by ~18 F1 points.

References

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Cited By

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Noui MLakhfif ALaouadi M(2025)Event Detection and Classification in Tweets using Deep LearningEngineering, Technology & Applied Science Research10.48084/etasr.923815:1(19977-19982)Online publication date: 2-Feb-2025
https://doi.org/10.48084/etasr.9238
Javed MAslam MKhurshid S(2025)An Intelligent Model for Parametric Cognitive Assessment of E-Learning-Based StudentsInformation10.3390/info1602009316:2(93)Online publication date: 26-Jan-2025
https://doi.org/10.3390/info16020093
Sharma DNath TGupta VSingh V(2025)Hate Speech Detection Research in South Asian Languages: A Survey of Tasks, Datasets and MethodsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/3711710Online publication date: 8-Jan-2025
https://doi.org/10.1145/3711710
Show More Cited By

Index Terms

Deep Learning for Hate Speech Detection in Tweets
1. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools
      1. Social networking sites
  2. World Wide Web
    1. Web applications
      1. Social networks
    2. Web mining

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During the COVID-19 pandemic, online social media platforms such as Twitter facilitate the exchange of information among people. However, the prevalence of “infodemic” such as online hate speech has exacerbated social rifts, discrimination, ...
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Published In

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

April 2017

1738 pages

ISBN:9781450349147

General Chairs:
Rick Barrett
W3Events
,
Rick Cummings
Murdoch University
,
Program Chairs:
Eugene Agichtein
Emory University
,
Evgeniy Gabrilovich
Google Research

In-Cooperation

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

Publisher

International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 03 April 2017

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WWW '17

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IW3C2

WWW '17: 26th International World Wide Web Conference

April 3 - 7, 2017

Perth, Australia

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WWW '17 Companion Paper Acceptance Rate 164 of 966 submissions, 17%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Noui MLakhfif ALaouadi M(2025)Event Detection and Classification in Tweets using Deep LearningEngineering, Technology & Applied Science Research10.48084/etasr.923815:1(19977-19982)Online publication date: 2-Feb-2025
https://doi.org/10.48084/etasr.9238
Javed MAslam MKhurshid S(2025)An Intelligent Model for Parametric Cognitive Assessment of E-Learning-Based StudentsInformation10.3390/info1602009316:2(93)Online publication date: 26-Jan-2025
https://doi.org/10.3390/info16020093
Sharma DNath TGupta VSingh V(2025)Hate Speech Detection Research in South Asian Languages: A Survey of Tasks, Datasets and MethodsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/3711710Online publication date: 8-Jan-2025
https://doi.org/10.1145/3711710
Alkhatib MFaisal AAlfalasi FShaalan KMohmed A(2025)Deep Learning Approaches for Detecting Arabic Cyberbullying Social MediaProcedia Computer Science10.1016/j.procs.2024.10.201244:C(278-286)Online publication date: 7-Jan-2025
https://dl.acm.org/doi/10.1016/j.procs.2024.10.201
Yuan LRizoiu M(2025)Generalizing Hate Speech Detection Using Multi-Task LearningComputer Speech and Language10.1016/j.csl.2024.10169089:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.csl.2024.101690
Narula RChaudhary P(2025)A comprehensive review on detection of hate speech for multi-lingual dataSocial Network Analysis and Mining10.1007/s13278-024-01401-y14:1Online publication date: 11-Jan-2025
https://doi.org/10.1007/s13278-024-01401-y
Reddy AGupta MPriya SReddy HDholvan M(2025)Detection of Abusive Content Using Machine Learning and Deep Learning MethodsAdvances in Data and Information Sciences10.1007/978-981-97-7360-2_20(227-240)Online publication date: 3-Jan-2025
https://doi.org/10.1007/978-981-97-7360-2_20
Alhayan FAlmobarak MShalabi HAlshubaili LAlbatati RAlqahtani WAlhaidari N(2024)Detection of cyberhate speech towards female sport in the Arabic XspherePeerJ Computer Science10.7717/peerj-cs.213810(e2138)Online publication date: 27-Jun-2024
https://doi.org/10.7717/peerj-cs.2138
Alhazmi AMahmud RIdris NMohamed Abo MEke C(2024)A systematic literature review of hate speech identification on Arabic Twitter data: research challenges and future directionsPeerJ Computer Science10.7717/peerj-cs.196610(e1966)Online publication date: 2-Apr-2024
https://doi.org/10.7717/peerj-cs.1966
Nourollahi SBaradaran RAmirkhani H(2024)Domain adaptation-based method for improving generalization of hate speech detection modelsSignal and Data Processing10.61186/jsdp.21.1.12521:1(125-142)Online publication date: 1-Jun-2024
https://doi.org/10.61186/jsdp.21.1.125
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Recommendations

Hate Speech Detection in Roman Urdu

Learning to Classify Hate and Extremism Promoting Tweets

A cross-lingual transfer learning method for online COVID-19-related hate speech detection

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