Racism, Hate Speech, and Social Media: A Systematic Review and Critique

Matamoros-Fernández, Ariadna; Farkas, Johan

doi:10.1177/1527476420982230

Cited by 212 publications

(117 citation statements)

References 75 publications

(115 reference statements)

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“…Social media activities may also contribute to the polarization of political debates and stoke incivility in the public sphere (Stella et al, 2018;Theocharis et al, 2016). They have demonstrably enabled hate speech, harassment, and trolling, especially oriented toward women and minorities too (Matamoros-Fernández & Farkas, 2021;Sobieraj, 2020;Stecklow, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections

Majó-Vázquez

Congosto

Nicholls

et al. 2021

Social Media + Society

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Content moderation on social media is at the center of public and academic debate. In this study, we advance our understanding on which type of election-related content gets suspended by social media platforms. For this, we assess the behavior and content shared by suspended accounts during the most important elections in Europe in 2017 (in France, the United Kingdom, and Germany). We identify significant differences when we compare the behavior and content shared by Twitter suspended accounts with all other active accounts, including a focus on amplifying divisive issues like immigration and religion and systematic activities increasing the visibility of specific political figures (often but not always on the right). Our analysis suggests that suspended accounts were overwhelmingly human operated and no more likely than other accounts to share “fake news.” This study sheds light on the moderation policies of social media platforms, which have increasingly raised contentious debates, and equally importantly on the integrity and dynamics of political discussion on social media during major political events.

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Section: Literature Reviewmentioning

confidence: 99%

The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections

Majó-Vázquez

Congosto

Nicholls

et al. 2021

Social Media + Society

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“…Hate speech detection is usually addressed as a supervised classification problem, where models are trained to distinguish between examples of hate and normal speech. A systematic literature review of academic articles on hate speech on social media, between 2014 and 2018 (Matamoros-Fernández and Farkas 2021 ), found that research was limited to text-based analyses of racist hate speech, to the Twitter platform, and to the content mostly from the U.S.…”

Section: Introductionmentioning

confidence: 99%

Evolution of topics and hate speech in retweet network communities

et al. 2021

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Twitter data exhibits several dimensions worth exploring: a network dimension in the form of links between the users, textual content of the tweets posted, and a temporal dimension as the time-stamped sequence of tweets and their retweets. In the paper, we combine analyses along all three dimensions: temporal evolution of retweet networks and communities, contents in terms of hate speech, and discussion topics. We apply the methods to a comprehensive set of all Slovenian tweets collected in the years 2018–2020. We find that politics and ideology are the prevailing topics despite the emergence of the Covid-19 pandemic. These two topics also attract the highest proportion of unacceptable tweets. Through time, the membership of retweet communities changes, but their topic distribution remains remarkably stable. Some retweet communities are strongly linked by external retweet influence and form super-communities. The super-community membership closely corresponds to the topic distribution: communities from the same super-community are very similar by the topic distribution, and communities from different super-communities are quite different in terms of discussion topics. However, we also find that even communities from the same super-community differ considerably in the proportion of unacceptable tweets they post.

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“…Data samples are collected from various sources on the Web (Table 3). Twitter is used in majority due to its popularity and the easiness to get data, while other social media (Formspring, YouTube, MySpace, Wikipedia, and Facebook) are used less [167]. Various sites such as the news website Gazzetta.it [198] usually specialized in one topic such as sport or politics and discussion forums such as voat, 4chan, or reddit are also investigated.…”

Section: Data Retrievalmentioning

confidence: 99%

Automatic Identification of Harmful, Aggressive, Abusive, and Offensive Language on the Web: A Survey of Technical Biases Informed by Psychology Literature

Balayn

Yang

Szlávik

et al. 2021

Trans. Soc. Comput.

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The automatic detection of conflictual languages (harmful, aggressive, abusive, and offensive languages) is essential to provide a healthy conversation environment on the Web. To design and develop detection systems that are capable of achieving satisfactory performance, a thorough understanding of the nature and properties of the targeted type of conflictual language is of great importance. The scientific communities investigating human psychology and social behavior have studied these languages in details, but their insights have only partially reached the computer science community. In this survey, we aim both at systematically characterizing the conceptual properties of online conflictual languages, and at investigating the extent to which they are reflected in state-of-the-art automatic detection systems. Through an analysis of psychology literature, we provide a reconciled taxonomy that denotes the ensemble of conflictual languages typically studied in computer science. We then characterize the conceptual mismatches that can be observed in the main semantic and contextual properties of these languages and their treatment in computer science works; and systematically uncover resulting technical biases in the design of machine learning classification models and the dataset created for their training. Finally, we discuss diverse research opportunities for the computer science community and reflect on broader technical and structural issues.

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Racism, Hate Speech, and Social Media: A Systematic Review and Critique

Cited by 212 publications

References 75 publications

The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections

The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections

Evolution of topics and hate speech in retweet network communities

Automatic Identification of Harmful, Aggressive, Abusive, and Offensive Language on the Web: A Survey of Technical Biases Informed by Psychology Literature

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