Analyzing the Targets of Hate in Online Social Media

Proceedings of the International AAAI Conference on Web and Social MediaPublished 4 August 2021Open access

Leandro Silva, Mainack Mondal, Denzil Correa, Fabrício Benevenuto, Ingmar Weber

DOI10.1609/icwsm.v10i1.14811

Citations152

TL;DR

This paper provides the first of a kind systematic large scale measurement study of the main targets of hate speech in online social media, gathering traces from two social media systems: Whisper and Twitter and developing and validate a methodology to identify hate speech on both these systems.

Abstract

Social media systems allow Internet users a congenial platform to freely express their thoughts and opinions. Although this property represents incredible and unique communication opportunities, it also brings along important challenges. Online hate speech is an archetypal example of such challenges. Despite its magnitude and scale, there is a significant gap in understanding the nature of hate speech on social media. In this paper, we provide the first of a kind systematic large scale measurement study of the main targets of hate speech in online social media. To do that, we gather traces from two social media systems: Whisper and Twitter. We then develop and validate a methodology to identify hate speech on both these systems. Our results identify online hate speech forms and offer a broader understanding of the phenomenon, providing directions for prevention and detection approaches.

Keywords

Computer ScienceSocial Sciences

Hate Speech Detection with Comment Embeddings

712 Citations2015Nemanja Djuric, Jing Zhou +4 more

This work proposes to learn distributed low-dimensional representations of comments using recently proposed neural language models, that can then be fed as inputs to a classification algorithm, resulting in highly efficient and effective hate speech detectors.

Policy & InternetCyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making

596 Citations2015Pete Burnap, Matthew Williams

It is demonstrated how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of cyber hate in a sample of Twitter data.

View PDF

Detecting Hate Speech on the World Wide Web

514 Citations2012William B. Warner, Julia Hirschberg

The definition of hate speech, the collection and annotation of the hate speech corpus, and a mechanism for detecting some commonly used methods of evading common "dirty word" filters are described.

International Journal of Multimedia and Ubiquitous EngineeringA Lexicon-based Approach for Hate Speech Detection

495 Citations2015Njagi Dennis Gitari, Zuping Zhang +2 more

The goal of the research is to create a model classifier that uses sentiment analysis techniques and in particular subjectivity detection to not only detect that a given sentence is subjective but also to identify and rate the polarity of sentiment expressions.

Proceedings of the AAAI Conference on Artificial IntelligenceLocate the Hate: Detecting Tweets against Blacks

457 Citations2013Irene Kwok, Yuzhou Wang

A supervised machine learning approach is applied, employing inexpensively acquired labeled data from diverse Twitter accounts to learn a binary classifier for the labels “racist” and “nonracist", which has a 76% average accuracy on individual tweets, suggesting that with further improvements, this work can contribute data on the sources of anti-black hate speech.

View PDF

Proceedings of the International AAAI Conference on Web and Social MediaThe Many Shades of Anonymity: Characterizing Anonymous Social Media Content

93 Citations2021Denzil Correa, Leandro Silva +3 more

The notion of anonymity sensitivity of a social media post is introduced, which captures the extent to which users think the post should be anonymous and a human annotator based methodology is proposed to measure the same for Whisper and Twitter posts.

View PDF

First Monday#Hashtagging hate: Using Twitter to track racism online

88 Citations2015Irfan Chaudhry

This paper considers three different projects that have used Twitter to track racist language in Canada, and highlights why Twitter is an important data collection tool for researchers interested in studying race and racism.

View PDF