Online Hate Speech and the Radical Right in Times of Pandemic: The Italian and English Cases

Caiani, Manuela; Carlotti, Benedetta; Padoan, Enrico

doi:10.1080/13183222.2021.1922191

Cited by 19 publications

(16 citation statements)

References 36 publications

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“…We discussed literature that showed that both COVID-19 protest groups and the far right were deplatformed from mainstream media, driving them toward platforms such as Telegram. Literature that has studied the far right has identified narratives that seek to connect to COVID-19 protests ( Caiani et al, 2021 ) but the extent to which COVID-19 groups contain or engage with far-right contents has not been examined, and this is what the present study sought to do. Theoretically, we used the framework of the mediation opportunity structure ( Cammaerts, 2012 ), which posits that movements mobilize by making use of discursive opportunity structures to develop and disseminate counternarratives; network opportunity structures, which help them grow and recruit members; and media opportunity structures, by which mainstream media pick up on the movement discourses and demands.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, research on the links between anti-lockdown, vaccine skepticism, anti-masking rhetoric, and the far right has tended to focus on mainstream social media, such as Twitter. For example, research by Caiani et al (2021) on British and Italian far-right politicians and their COVID rhetoric on Twitter found that COVID offered them the opportunity to reframe their traditional friend and enemy categories while also reinforcing their relationship with their bases.…”

Section: Social Media Covid-19 and The Far Rightmentioning

confidence: 99%

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Covid-19 Protesters and the Far Right on Telegram: Co-Conspirators or Accidental Bedfellows?

Curley

Σιαπέρα

Carthy

2022

Social Media + Society

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The COVID-19 pandemic led to the creation of a new protest movement, positioned against government lockdowns, mandatory vaccines, and related measures. Efforts to control misinformation by digital platforms resulted in take downs of key accounts and posts. This led some of these protest groups to migrate to platforms with less stringent content moderation policies, such as Telegram. Telegram has also been one of the destinations of the far right, whose deplatforming from mainstream platforms began a few years ago. Given the co-existence of these two movements on Telegram, the article examines their connections. Empirically, the article focused on Irish Telegram groups and channels, identifying relevant protest movements and collecting their posts. Using computational social science methods, we examine whether far-right terms and discourses are present and how this varies across different clusters of Telegram Covid-19 protest groups. In addition, we examine which actors are posting far-right content and what kind of roles they play in the network of Telegram groups. The findings indicate the presence of far-right discourses among the COVID-19 groups. However, the existence of these groups was not solely driven by the extreme right, and the incidence of far-right discourses was not equal across all COVID-19 protest groups. We interpret these findings under the prism of the mediation opportunity structure: while the far right appears to have taken advantage of the network opportunity structure afforded by deplatforming and the migration to Telegram, it did not succeed in diffusing its ideas widely among the COVID-19 protest groups in the Irish Telegram.

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Section: Discussionmentioning

confidence: 99%

Section: Social Media Covid-19 and The Far Rightmentioning

confidence: 99%

Covid-19 Protesters and the Far Right on Telegram: Co-Conspirators or Accidental Bedfellows?

Curley

Σιαπέρα

Carthy

2022

Social Media + Society

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“…German media on Facebook accused migrants of spreading the virus to locals ( Boberg et al, 2020 ), while fake news stories that ethnic minorities are immune were diffused through traditional and social media in Italy ( De Nardi and Phillips, 2021 ). Again in Italy, but also in the UK, the radical right used Twitter to spread antimigrant hate speech as part of a wider populist agenda ( Caiani et al, 2021 ).…”

Section: Predominant Representations Of Migration In Traditional and ...mentioning

confidence: 99%

Migrant Racialization on Twitter during a border and a pandemic crisis

Avraamidou

Eftychiou²

2021

International Communication Gazette

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This work examines how the outbreak of the COVID-19 pandemic reshaped the migration debate on Twitter. Through co-hashtag network analysis, time-frequency and content analysis, it shows that the pandemic was related with positive (humanitarian) and negative (threat) stances about migration. The positive side focused on the need to protect refugees stranded at camps in Greece from COVID-19. The negative focused on the Greek-Turkish land-border crisis (Evros crisis), using COVID-19 to reinforce migrants as racialized others. These findings fit the problematization of positive and negative migrant representations in the Global north as Eurocentric. In the case of camps, refugees fit well within the victim/helpless frame, justifying humanitarianism, this time on health grounds. Regarding the border crisis, refugees also fit the Eurocentric frame of violent/male/inferior other who could spread a deadly virus. Overall, COVID-19 intertwined with migration in Twitter debates, reinforcing the racialized, Eurocentric representational field on migrants from the Global south.

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“…The advent of social media has democratized public discourse on an unparalleled scale. Meanwhile, it is considered a particularly conducive arena for hate speech (Caiani et al, 2021). Online hate speech is prevalent and can lead to serious consequences.…”

Section: Introductionmentioning

confidence: 99%

Hate Speech and Counter Speech Detection: Conversational Context Does Matter

Yu¹,

Blanco²,

Hong³

2022

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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Hate speech is plaguing the cyberspace along with user-generated content. This paper investigates the role of conversational context in the annotation and detection of online hate and counter speech, where context is defined as the preceding comment in a conversation thread. We created a context-aware dataset for a 3-way classification task on Reddit comments: hate speech, counter speech, or neutral. Our analyses indicate that context is critical to identify hate and counter speech: human judgments change for most comments depending on whether we show annotators the context. A linguistic analysis draws insights into the language people use to express hate and counter speech. Experimental results show that neural networks obtain significantly better results if context is taken into account. We also present qualitative error analyses shedding light into (a) when and why context is beneficial and (b) the remaining errors made by our best model when context is taken into account.

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Online Hate Speech and the Radical Right in Times of Pandemic: The Italian and English Cases

Cited by 19 publications

References 36 publications

Covid-19 Protesters and the Far Right on Telegram: Co-Conspirators or Accidental Bedfellows?

Covid-19 Protesters and the Far Right on Telegram: Co-Conspirators or Accidental Bedfellows?

Migrant Racialization on Twitter during a border and a pandemic crisis

Hate Speech and Counter Speech Detection: Conversational Context Does Matter

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