Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech

Concerning individual or institutional accountability for online hate speech, research has revealed that most such speech is covert (veiled or camouflaged expressions of hate) and cannot be addressed with existing measures (e.g., deletion of messages, prosecution of the perpetrator). Therefore, in t...

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Main Author: Fabienne Baider
Format: Article
Language:English
Published: Cogitatio 2023-05-01
Series:Politics and Governance
Subjects:
Online Access:https://www.cogitatiopress.com/politicsandgovernance/article/view/6465
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author Fabienne Baider
author_facet Fabienne Baider
author_sort Fabienne Baider
collection DOAJ
description Concerning individual or institutional accountability for online hate speech, research has revealed that most such speech is covert (veiled or camouflaged expressions of hate) and cannot be addressed with existing measures (e.g., deletion of messages, prosecution of the perpetrator). Therefore, in this article, we examine another way to respond to and possibly deflect hate speech: counter-speech. Counter-narratives aim to influence those who write hate speech, to encourage them to rethink their message, and to offer to all who read hate speech a critical deconstruction of it. We created a unique set of parameters to analyze the strategies used in counter-speech and their impact. Upon analysis of our database (manual annotations of 15,000 Twitter and YouTube comments), we identified the rhetoric most used in counter-speech, the general impact of the various counter-narrative strategies, and their specific impact concerning several topics. The impact was defined by noting the number of answers triggered by the comment and the tone of the answers (negative, positive, or neutral). Our data reveal an overwhelming use of argumentative strategies in counter-speech, most involving reasoning, history, statistics, and examples. However, most of these argumentative strategies are written in a hostile tone and most dialogues triggered are negative. We also found that affective strategies (based on displaying positive emotions, for instance) led to a positive outcome, although in most cases these narratives do not receive responses. We recommend that education or training—even machine learning such as empathetic bots—should focus on strategies that are positive in tone, acknowledging grievances especially.
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spelling doaj.art-80ad3d465ccc4bc68027954f8047cdd12023-05-17T09:00:59ZengCogitatioPolitics and Governance2183-24632023-05-0111224926010.17645/pag.v11i2.64652954Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐SpeechFabienne Baider0Department of French and European Studies, University of Cyprus, CyprusConcerning individual or institutional accountability for online hate speech, research has revealed that most such speech is covert (veiled or camouflaged expressions of hate) and cannot be addressed with existing measures (e.g., deletion of messages, prosecution of the perpetrator). Therefore, in this article, we examine another way to respond to and possibly deflect hate speech: counter-speech. Counter-narratives aim to influence those who write hate speech, to encourage them to rethink their message, and to offer to all who read hate speech a critical deconstruction of it. We created a unique set of parameters to analyze the strategies used in counter-speech and their impact. Upon analysis of our database (manual annotations of 15,000 Twitter and YouTube comments), we identified the rhetoric most used in counter-speech, the general impact of the various counter-narrative strategies, and their specific impact concerning several topics. The impact was defined by noting the number of answers triggered by the comment and the tone of the answers (negative, positive, or neutral). Our data reveal an overwhelming use of argumentative strategies in counter-speech, most involving reasoning, history, statistics, and examples. However, most of these argumentative strategies are written in a hostile tone and most dialogues triggered are negative. We also found that affective strategies (based on displaying positive emotions, for instance) led to a positive outcome, although in most cases these narratives do not receive responses. We recommend that education or training—even machine learning such as empathetic bots—should focus on strategies that are positive in tone, acknowledging grievances especially.https://www.cogitatiopress.com/politicsandgovernance/article/view/6465accountabilityargumentative strategiescounter‐speechcovert hate speechemotional appeal
spellingShingle Fabienne Baider
Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
Politics and Governance
accountability
argumentative strategies
counter‐speech
covert hate speech
emotional appeal
title Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
title_full Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
title_fullStr Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
title_full_unstemmed Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
title_short Accountability Issues, Online Covert Hate Speech, and the Efficacy of Counter‐Speech
title_sort accountability issues online covert hate speech and the efficacy of counter speech
topic accountability
argumentative strategies
counter‐speech
covert hate speech
emotional appeal
url https://www.cogitatiopress.com/politicsandgovernance/article/view/6465
work_keys_str_mv AT fabiennebaider accountabilityissuesonlinecoverthatespeechandtheefficacyofcounterspeech