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Following Sahana Udupa and Matti Pohjonen’s (2019) invitation to move the debate beyond a normative understanding of hate speech, this article seeks to build a foundation for conceptual and empirical inquiry of speech commonly considered deviant and disturbing. It develops in three stages. It first maps the public lives of terms that refer to online vitriol and how they have been used by different communities of researchers, politicians, advocacy groups, and national organizations. Second, it shows how different types of “haters” have been interpreted as parts of “swarms” or “armies,” depending on whether their violent potential emerges around critical incidents or whether they respond to longer-term strategies through which communities and their leaders tie their speech acts to explicit narratives. The article concludes by locating “extreme speech” within this broader conceptual tapestry, arguing that the paternalistic the gaze that characterizes a lot of research on online hate speech is tied to what Chantal Mouffe has referred to as the “moralization of politics,” a phenomenon that cannot be matched by responses that are themselves moral.

The opportunities afforded by the Internet greatly overshadow the challenges. While not forgetting this, we can nevertheless still address some of the problems that arise. Hate speech online is one such problem. But what exactly is hate speech online, and how can we deal with it effectively? As with freedom of expression, on- or offline, UNESCO defends the position that the free flow of information should always be the norm. Counter-speech is generally preferable to suppression of speech. And any response that limits speech needs to be very carefully weighed to ensure that this remains wholly exceptional, and that legitimate robust debate is not curtailed. A typology of responses is elaborated in this study.

VOX-Pol Blog post.

Social media platforms are popular for expressing personal views, emotions and beliefs. Social media platforms are influential for propagating extremist ideologies for group-building, fund-raising, and recruitment. To monitor and control the outreach of extremists on social media, detection of extremism in social media is necessary. The existing extremism detection literature on social media is limited by specific ideology, subjective validation methods, and binary or tertiary classification. A comprehensive and comparative survey of datasets, classification techniques, validation methods with online extremism detection tool is essential. The systematic literature review methodology (PRISMA) was used. Sixty-four studies on extremism research were collected, including 31 from SCOPUS, Web of Science (WoS), ACM, IEEE, and 33 thesis, technical and analytical reports using Snowballing technique. The survey highlights the role of social media in propagating online radicalization and the need for extremism detection on social media platforms. The review concludes lack of publicly available, class-balanced, and unbiased datasets for better detection and classification of social-media extremism. Lack of validation techniques to evaluate correctness and quality of custom data sets without human interventions, was found. The information retrieval unveiled that contemporary research work is prejudiced towards ISIS ideology. We investigated that deep learning based automated extremism detection techniques outperform other techniques. The review opens the research opportunities for developing an online, publicly available automated tool for extremism data collection and detection. The survey results in conceptualization of architecture for construction of multi-ideology extremism text dataset with robust data validation techniques for multiclass classification of extremism text.

Social media platforms are popular for expressing personal views, emotions and beliefs. Social media platforms are influential for propagating extremist ideologies for group-building, fund-raising, and recruitment. To monitor and control the outreach of extremists on social media, detection of extremism in social media is necessary. The existing extremism detection literature on social media is limited by specific ideology, subjective validation methods, and binary or tertiary classification. A comprehensive and comparative survey of datasets, classification techniques, validation methods with online extremism detection tool is essential. The systematic literature review methodology (PRISMA) was used. Sixty-four studies on extremism research were collected, including 31 from SCOPUS, Web of Science (WoS), ACM, IEEE, and 33 thesis, technical and analytical reports using Snowballing technique. The survey highlights the role of social media in propagating online radicalization and the need for extremism detection on social media platforms. The review concludes lack of publicly available, class-balanced, and unbiased datasets for better detection and classification of social-media extremism. Lack of validation techniques to evaluate correctness and quality of custom data sets without human interventions, was found. The information retrieval unveiled that contemporary research work is prejudiced towards ISIS ideology. We investigated that deep learning based automated extremism detection techniques outperform other techniques. The review opens the research opportunities for developing an online, publicly available automated tool for extremism data collection and detection. The survey results in conceptualization of architecture for construction of multi-ideology extremism text dataset with robust data validation techniques for multiclass classification of extremism text.

This paper observes some of the most distinguished characteristics of the Islamic State related to the use of modern technology and tries to drawn some important conclusions between the terrorist’s quasi state, modernity and technology. After the examination of the functioning of IS at the peak of its powers between 2014 and 2017, the analysis turns to terrorists’ various online activities. All of them are showing the Islamic State’s reliance on modern technology, especially IT, as one of the most important aspects of its terrorist activities that greatly contributed not only to the effectiveness, but to the essential definition of first modern terrorist quasi-state. The second part of the paper deals with the Islamic State`s fully reliance on technology in its own legitimization (both among Islamist rivals and “infidels”). The celebration and the fascination with modern technology as main IS characteristics make it different from other Islamist terrorist groups, and trying to establish relations between modernity and terrorism based on religious fundamentalism. The paper also tries to find answers to the question whether IS’s ultra-modern techno approach is responsible for its transformation from a classical fundamentalist terrorist group into some kind of modern political ideology and a social movement with totalitarian and murderous characteristics.