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1
Banks, James. "Regulating hate speech online." International Review of Law, Computers & Technology 24, no. 3 (October 29, 2010): 233–39. http://dx.doi.org/10.1080/13600869.2010.522323.
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Schneiders, Pascal. "Hate Speech auf Online-Plattformen." UFITA 85, no. 2 (2021): 269–333. http://dx.doi.org/10.5771/2568-9185-2021-2-269.
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Hate Speech scheint Facebook, Twitter, Telegram und Co. zu durchdringen und ruft daher vermehrt nationale und supranationale Vorstöße zur Regulierung digitaler Plattformen auf den Plan. Das jüngste aufsehenerregende Vorhaben ist der Digital Services Act, der EU-weit abgestufte Moderations-, Transparenz- und andere Sorgfaltspflichten für digitale Plattformen vorsieht. Die geplante Verordnung wird zum Anlass genommen, zunächst aus kommunikationswissenschaftlicher Sicht umfassend Ursachen, Verbreitung und Effekte von Hate Speech darzustellen und auf diesem Wege den Regulierungsbedarf zu verdeutlichen. Daraufhin wird auf die im vorgeschlagenen Digital Services Act aufgeworfenen Maßnahmen eingegangen und im Vergleich mit dem Netzwerkdurchsetzungsgesetz erörtert, inwieweit der Digital Services Act das Problem Hate Speech adressiert. Den Abschluss bilden Empfehlungen für den künftigen wissenschaftlichen und regulatorischen Umgang mit Hate Speech.
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Rusieshvili-Cartledge, Manana, and Rusudan Dolidze. "Hate Speech in Online Polylogues." FLEKS - Scandinavian Journal of Intercultural Theory and Practice 7, no. 1 (February 13, 2021): 43–59. http://dx.doi.org/10.7577/fleks.4171.
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This research is the first attempt in Georgia to analyse hate speech emerging in Computer-Meditated Communication. Particular attention is paid to the polylogal, asynchronic remarks made by members of the public reacting to online newspaper articles or press releases concerning the LGPT pride event planned for 18 - 23 June 2019, in Tbilisi, Georgia. The methodology is based on combining methods utilized in CDA and Genre Approach to (im)politeness which is in accord with the general approach to CMDA . At the first stage of the analysis, the examples of hate-speech acts were analysed according to the following criteria: identification of linguistic means and strategies employed while expressing impoliteness and specificity of identity construction (self-asserted versus others -asserted, positive versus negative, roles of participants and strategies of conflict generation or management). Next, linguistic peculiarities of hate speech (for instance, linguistic triggers [threats, insults, sarcasm incitements], wordplay, taboo, swear and derogatory words, metaphors, allusions and similes) were identified and analysed. Quantitative methodology was employed while stating the number of proponents and opponents of the event as well as statistical data referring to the number of linguistic and politeness strategies employed while expressing an opinion. This research shows particular tendencies of how impoliteness can be realised and how social identities can be construed using the example of hate discourse concerning LGBT pride in Georgia. However, to fully explore the genre properties of hate discourse in Georgia further research based on examples of hate-discourse strategies applied when discussing ethnic minorities and gender roles, is needed.
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Lupu, Yonatan, Richard Sear, Nicolas Velásquez, Rhys Leahy, Nicholas Johnson Restrepo, Beth Goldberg, and Neil F. Johnson. "Offline events and online hate." PLOS ONE 18, no. 1 (January 25, 2023): e0278511. http://dx.doi.org/10.1371/journal.pone.0278511.
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Online hate speech is a critical and worsening problem, with extremists using social media platforms to radicalize recruits and coordinate offline violent events. While much progress has been made in analyzing online hate speech, no study to date has classified multiple types of hate speech across both mainstream and fringe platforms. We conduct a supervised machine learning analysis of 7 types of online hate speech on 6 interconnected online platforms. We find that offline trigger events, such as protests and elections, are often followed by increases in types of online hate speech that bear seemingly little connection to the underlying event. This occurs on both mainstream and fringe platforms, despite moderation efforts, raising new research questions about the relationship between offline events and online speech, as well as implications for online content moderation.
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Mathew, Binny, Punyajoy Saha, Hardik Tharad, Subham Rajgaria, Prajwal Singhania, Suman Kalyan Maity, Pawan Goyal, and Animesh Mukherjee. "Thou Shalt Not Hate: Countering Online Hate Speech." Proceedings of the International AAAI Conference on Web and Social Media 13 (July 6, 2019): 369–80. http://dx.doi.org/10.1609/icwsm.v13i01.3237.
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Hate content in social media is ever increasing. While Facebook, Twitter, Google have attempted to take several steps to tackle the hateful content, they have mostly been unsuccessful. Counterspeech is seen as an effective way of tackling the online hate without any harm to the freedom of speech. Thus, an alternative strategy for these platforms could be to promote counterspeech as a defense against hate content. However, in order to have a successful promotion of such counterspeech, one has to have a deep understanding of its dynamics in the online world. Lack of carefully curated data largely inhibits such understanding. In this paper, we create and release the first ever dataset for counterspeech using comments from YouTube. The data contains 13,924 manually annotated comments where the labels indicate whether a comment is a counterspeech or not. This data allows us to perform a rigorous measurement study characterizing the linguistic structure of counterspeech for the first time. This analysis results in various interesting insights such as: the counterspeech comments receive much more likes as compared to the noncounterspeech comments, for certain communities majority of the non-counterspeech comments tend to be hate speech, the different types of counterspeech are not all equally effective and the language choice of users posting counterspeech is largely different from those posting non-counterspeech as revealed by a detailed psycholinguistic analysis. Finally, we build a set of machine learning models that are able to automatically detect counterspeech in YouTube videos with an F1-score of 0.71. We also build multilabel models that can detect different types of counterspeech in a comment with an F1-score of 0.60.
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Salvatore, Anggie Ray, I. Nyoman Suparwa, and Made Sri Satyawati. "Ujaran Kebencian dalam Kolom Komentar Media Berita Online BABE." Humanis 26, no. 1 (February 28, 2022): 125. http://dx.doi.org/10.24843/jh.2022.v26.i01.p13.
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Hate speech is a language phenomenon that often appears on social media nowadays. This was exacerbated by the political intensity between supporting and opposing groups of the government. The commentary column which contains news on the topic of government is one of the ways to spread hate speeches. Therefore, this study aims to analyze the hate speech that appears in the commentary column of an online news media called BABE with the aim of finding the form of lingual markers, the speech act meaning, and the speech act function of the hate speech. The results of this study found that lingual markers in hate speech were divided into three categories, namely words, phrases and utterances. The meaning of hate speech is illocutionary and is classified into seven types of hate speech, including insult, defamation, desecration, unpleasant action, provocation, incitement, and hoax. Meanwhile, the speech act function that appears in hate speech has four speech act functions, namely the assertive function, the directive function, the commissive function, and the expressive function.
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Cho, Je Seong, and Youn oh Cho. "A Study on Online Hate Speech and Offline Hate Speech Relationship." Korean Association of Criminal Psychology 15, no. 2 (June 30, 2019): 23–36. http://dx.doi.org/10.25277/kcpr.2019.15.2.23.
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Baider, Fabienne, and Maria Constantinou. "Covert hate speech." Journal of Language Aggression and Conflict 8, no. 2 (July 15, 2020): 262–87. http://dx.doi.org/10.1075/jlac.00040.bai.
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Abstract Previous research on extremist discourse has revealed that racism is linguistically shaped by its socio-cultural context. For instance, a comparison between Greek Cypriot and Greek online data indicated that the two communities use different linguistic means and strategies to express their aversion to the Other, and that Greek comments are more overtly insulting than Greek Cypriot comments (Baider and Constantinou 2017a; Assimakopoulos and Baider 2019). The present study focuses on how irony is used to disseminate hate speech, albeit covertly. Our dataset comprises online Greek and Greek Cypriot comments posted on social media and collected during the same period of time (2015- 2016) within an EU project. We use concepts such as verisimilitude and overt untruthfulness to deconstruct ironic racist comments. We conclude that irony in both datasets fulfils three socio-pragmatic functions: it serves to insult or humiliate members of groups targeted for their ethnic identity; it creates or reinforces negative feelings against such groups; it promotes beliefs that could be used to legitimate their mistreatment. Regarding socio-cultural differences, it emerges that the use of the Greek Cypriot vernacular and the appeal to indigenous in-group social stereotypes influence the way irony shapes racist comments and reinforces in-group membership.
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Das, Mithun, Binny Mathew, Punyajoy Saha, Pawan Goyal, and Animesh Mukherjee. "Hate speech in online social media." ACM SIGWEB Newsletter, Autumn (November 24, 2020): 1–8. http://dx.doi.org/10.1145/3427478.3427482.
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Reed, Chris. "The challenge of hate speech online." Information & Communications Technology Law 18, no. 2 (July 2009): 79–82. http://dx.doi.org/10.1080/13600830902812202.
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Vasilenko, Ekaterina. "Sexist hate speech: Topical organization of intolerant discourse." Językoznawstwo 14, no. 1(14)/2020 (March 22, 2021): 47–60. http://dx.doi.org/10.25312/2391-5137.14/2020_03ev.
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The article is aimed at determining the topical structure of sexist hate speech as a form of intolerant discourse. Sexist hate speech is viewed as a type of gender-based hate speech that is influenced by the same social, political and legal, cultural and ethical factors as sexual orientation-based or gender identity-based hate speech. The article proposes a topical structure of hate speech in general and provides examples of sexist hate speech topics and subtopics in Belarusian online discourse. Keywords: hate speech, sexist hate speech, gender-based hate speech, discourse of hate, intolerant discourse, online discourse, topic.
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Muhič Dizdarevič, Selma. "Scope, Structure, Aspects of Antigypsyist Hate Speech Online." Transdigital 2, no. 4 (November 5, 2021): 1–20. http://dx.doi.org/10.56162/transdigital79.
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This article aims to provide the relevant parameters of the phenomena of antigypsyism, online hate speech, and their connection. The parameters serve as background for finding out about the trends in online hate speech directed at the Roma community, the most important concepts and tropes regarding antigypsyism, and the relevant trends in antigypsyist online hate speech. The article will focus on the European Union context because it provides a comparative political and legal framework and possibilities of joint activities and policies to tackle Roma discrimination. By combining scholarly resources and governmental reports, monitoring and reporting collected through nongovernmental organizations, it is concluded that the phenomenon of online antigypsyism is getting stronger. It mirrors offline hate speech and is relatively poorly monitored. It is spread via all mainstream social media platforms whose record on its removal tends to oscillate. A brief section is dedicated to intersectional aspects of antigypsyist hate speech whose iterations in the digital space are under-researched.
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Baider, Fabienne. "Pragmatics lost?" Pragmatics and Society 11, no. 2 (July 13, 2020): 196–218. http://dx.doi.org/10.1075/ps.20004.bai.
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Abstract This article argues for a definition of online hate speech as a contextualised speech act that is part of a social process of alienation. It suggests that hate speech comes in degrees, is contextual, involves already existing power dynamics, and ‘others’ its targets by creating in/out groups. I first review the various stances towards understanding the phenomenon of online hate speech, including approaches that focus on online hate speech as an interaction shaped by its medium, while also emphasizing the need to consider the role of implicatures in speech acts when defining hate speech. Second, I argue that the relationality of online speech implies that any message is embedded in idiosyncratic socio-cultural norms, and that therefore a ‘one size fits all’ definition of hate speech is elusive. I conclude by suggesting that contextualized hate speech is embedded in a social process of alienation and should be understood as a continuum.
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Felberg, Tatjana, and Ljiljana Šarić. "Chocolate, identity, and extreme speech online." FLEKS - Scandinavian Journal of Intercultural Theory and Practice 7, no. 1 (February 12, 2021): 15–25. http://dx.doi.org/10.7577/fleks.4168.
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In this article the phrase “extreme speech” is used to encompass both hate speech and impoliteness. Legislation against hate speech has been passed in many countries, while work on defining phenomena related to hate speech is still ongoing. As a rule, there is no legislation prohibiting impoliteness, and thus impoliteness is often perceived as a less serious verbal offence. There is, however, a grey zone between the two phenomena, which depends on contextual factors that must be constantly explored. In this article, we explore the gray zone between hate speech and impoliteness by looking at user-generated posts commenting on seemingly uncontroversial topics such as giving chocolate to children. The context we explore is the political relationship between Croatia and Serbia, two neighboring countries in the southwest Balkans with a history of recent military conflicts that ended in 1995. The relationship between these two countries can still be described as periodically troubled. The comments we analyze were posted on two online newspapers, the Croatian Jutarnji list and the Serbian Večernje novosti. Using impoliteness theory and Critical Discourse Analysis framework we identify and analyze various linguistic means that serve as extreme speech triggers, connect them to relevant contexts and highlight the grey zone that exist between hate speech and impoliteness. Our findings show that, in their discussions, the posters used a number of linguistic means for constructing national identities that at times resulted in extreme speech. The posters often targeted individual co-posters first and very quickly moved on to target ethnic groups, thus fluctuating between impoliteness and hate speech.
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KASIANCZUK, MAKSYM. "HATE SPEECH TOWARDS LGBT IN UKRAINIAN ONLINE MEDIA." Sociology: Theory, Methods, Marketing, Stmm. 2022 (2) (2022): 138–61. http://dx.doi.org/10.15407/sociology2022.02.138.
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The article presents the results of a content-analytical study of 243 publications in online media of Ukraine during 2021 in comparison with the results of earlier monitorings of Ukrainian offline and online media. Analysis of both scientific literature shows that hate speech against minorities (in particular, LGBT) is an urgent issue that has a distinct practical dimension, because the spread of hate in the online environment can have the nature of an epidemic and be accompanied by an increase in violent acts. Although the results have a number of limitations (different ways of forming selective sets of media materials in the analyzed studies, lack of research consensus on the definition of hate speech, attribution of the collected data to the period before the beginning of the massive invasion of the Russian Federation troops on the territory of Ukraine and impossibility of reflecting the state of society in the war time), it showed that the number of news related to LGBT was decreasing, despite of media samples design. Publications containing hate speech were from 2 to 25%. Hate speech in these publications was usually quotes and does not express the position of the journalist. Hate speech arose in the context of both public and internal actions of the LGBT community and was accompanied by calls for violence or violence itself. Stronger hate speech was more typical for anonymous internet commentators, street hooligans (including those from organized right-wing gangs), and small local public figures. The collected materials are analyzed in the paradigm of R. Connell’s hierarchy of masculinities. Hate speech is characteristic primarily for the statements of athletes, military and politicians, that is, those who are associated in the public consciousness with the stereotypical image of a “real man”. In further studies, approaches to the formation of media samples should be standardized, as well as, the tools for automatic or semi-automatic content analysis should be developed. All this will facilitate the study of changes in hate speech in the public space.
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Kaczmarczyk, Barbara, Marlena Dąbrowska, Piotr Szczepański, and Izabela Nowicka. "Online Hate Speech and the Safety of Internet Users." Security Dimensions 31, no. 31 (September 30, 2019): 139–59. http://dx.doi.org/10.5604/01.3001.0014.0292.
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Background: Hate speech is a very important problem nowadays. One can meet it in one’s immediate surroundings (conversations with friends), the media, the Internet, or in the so-called public space (for example, inscriptions on the walls). One form of hate speech is online hate speech, which, together with certain other phenomena, is referred to as hejt in the Polish language. The authors of the article focus on presenting online hate speech in relation to various age and social groups. Objectives: The aim of the article is to present the phenomenon of hate speech on the web and its impact on the safety of Internet users. Methods: The article uses basic theoretical and empirical methods. Content published on the Internet is analyzed and case studies are described. Interviews with experts (psychologists, police officers, sociologists, media and hate speech specialists) were also conducted and their views are presented. Conclusions: In the discussion about hate speech, prevention is extremely important. According to the authors, broad prevention consisting of professionally prepared content, enriched with film materials, presented by an expert or a trained teacher, should be included in the core curriculum of schools as one of the mandatory issues raised during the lessons.
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Vasilenko, Ekaterina. "Tematicheskaya struktura intolerantnogodiskursa." Językoznawstwo 15, no. 1 (December 2021): 81–92. http://dx.doi.org/10.25312/2391-5137.15/2021_06ev.
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Thematic structure of the discourse of intolerance. The article presents a model of the thematic structure of hate speech as a form of intolerant discourse on vulnerable social groups singled out on the basis of protected characteristics. Four major thematic categories are identified: “Intuitive assessment”, “Characterization of the social group”, “Comparison of the group with other social groups” and “Position of the group in the discourse community”. Examples of verbalization of topics and subtopics of homophobic, sexist and xenophobic rhetoric in the online comments of Belarusian users in 2015–2019 are provided. Keywords: intolerant discourse, discourse of hate, hate speech, gender-based hate speech, sexist hate speech, xenophobic hate speech, sexual orientation-based hate speech, online discourse, online comment
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O’Regan, Catherine. "Hate Speech Online: an (Intractable) Contemporary Challenge?" Current Legal Problems 71, no. 1 (2018): 403–29. http://dx.doi.org/10.1093/clp/cuy012.
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Arofah, Kurnia. "Rhetorical Analysis of Hate Speech: Case Study of Hate Speech Related to Ahok’s Religion Blasphemy Case." Mediator: Jurnal Komunikasi 11, no. 1 (June 29, 2018): 91–105. http://dx.doi.org/10.29313/mediator.v11i1.3119.
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The discussion about hate speech is not something new. However, recently it becomes phenomenon that widely spoken. As something that naturally comes out as a human nature. Nowadays hate speech tends to be harmful because it is supported by new media such as online media and social media. This research try to discuss about hate speech related to religion blasphemy accusation that drags, Basuki Tjahaya Purnama known as Ahok into jail. This paper used qualitative method and rhetoric analysis to analyze the hate speech in online media news related to Ahok’s case. The results are, hate speech came from content posted in website such as online political opinion and news. From ethos aspect, most of the hate speech neglected the ethos aspect which provides the credibility and trustworthiness of the source.; from the pathos aspect, the author of the news are choosing words that triggered anger and negative emotion from its audience; from the logos aspect, most of the hate speech draws it’s readers to logical fallacy due to the lackness of facts of its conclusion claim. The Hate speech rhetoric neglects the ethos and logos aspects and it mostly rely on pathos aspect to persuade its readers for hating.
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Silva, Leandro, Mainack Mondal, Denzil Correa, Fabrício Benevenuto, and Ingmar Weber. "Analyzing the Targets of Hate in Online Social Media." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 1 (August 4, 2021): 687–90. http://dx.doi.org/10.1609/icwsm.v10i1.14811.
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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.
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Nielsen, Anne Birgitta, Ekaterine Pirtskhalava, and Ekaterine Basilaia. "Hate speech in intercultural encounters." FLEKS - Scandinavian Journal of Intercultural Theory and Practice 7, no. 1 (September 15, 2021): 2. http://dx.doi.org/10.7577/fleks.4570.
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The issue of hate speech has been a topic of international debate—most frequently in the domains of law, philosophy and language. Different issues linked to changes in society, ranging from the proliferation of social media, innovation and technology and influx of fake news, disinformation and propaganda to the rise of nationalism, far-right movements, increased cross-border movement of people and transnational business have made studying the conceptual and practical aspects of hate speech in different contexts ever more important. The papers in this issue focus on the sociolinguistic aspects of the use of hate speech and its different variants in online communication, offering a much-needed perspective on how hate speech in digital communication can be identified and tackled. For example, Dr. Manana Ruseishvili and Dr. Rusudan Dolidze analyse hate speech in computer-meditated communication, focusing on the polylogal, asynchronic remarks made by members of the public reacting to articles in online media or press releases about the LGBT pride event planned for June 2019. The research carried out by Lilit Bekaryan explores how hateful posts and comments can start among Facebook users, and studies the language means employed in their design based on data from more than ten open Facebook pages managed by popular Armenian figures, such as media experts, journalists, politicians and bloggers. Dr. Tatjana R. Felberg explores the interconnectedness between impoliteness and hate speech in online comments in Croatia and Serbia by applying impoliteness theory and a critical discourse analysis framework. Her research demonstrates that those who post often fluctuate between hate speech and impoliteness. Dr. Ayunts and Dr. Paronyan provide a comparative analysis of manifestations of hate speech and euphemisms in Armenian and British online media outlets and social sites targeting people's sexual orientation with emphasis on the interconnectedness of hate speech and culture. This issue was prepared as part of the project ‘Intercultural encounters in academia and work places in South Caucasus and Norway’ funded by DIKU, the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education. The project partner universities are Oslo Metropolitan University, Ivane Javakhishvili Tbilisi State University, Yerevan State University and Khazar University.
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SIEGEL, ALEXANDRA A., and VIVIENNE BADAAN. "#No2Sectarianism: Experimental Approaches to Reducing Sectarian Hate Speech Online." American Political Science Review 114, no. 3 (June 29, 2020): 837–55. http://dx.doi.org/10.1017/s0003055420000283.
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We use an experiment across the Arab Twittersphere and a nationally representative survey experiment in Lebanon to evaluate what types of counter-speech interventions are most effective in reducing sectarian hate speech online. We explore whether and to what extent messages priming common national identity or common religious identity, with and without elite endorsements, decrease the use of hostile anti-outgroup language. We find that elite-endorsed messages that prime common religious identity are the most consistently effective in reducing the spread of sectarian hate speech. Our results provide suggestive evidence that religious elites may play an important role as social referents—alerting individuals to social norms of acceptable behavior. By randomly assigning counter-speech treatments to actual producers of online hate speech and experimentally evaluating the effectiveness of these messages on a representative sample of citizens that might be incidentally exposed to such language, this work offers insights for researchers and policymakers on avenues for combating harmful rhetoric on and offline.
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Brown, Alexander. "What is so special about online (as compared to offline) hate speech?" Ethnicities 18, no. 3 (May 19, 2017): 297–326. http://dx.doi.org/10.1177/1468796817709846.
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There is a growing body of literature on whether or not online hate speech, or cyberhate, might be special compared to offline hate speech. This article aims to both critique and augment that literature by emphasising a distinctive feature of the Internet and of cyberhate that, unlike other features, such as ease of access, size of audience, and anonymity, is often overlooked: namely, instantaneousness. This article also asks whether there is anything special about online (as compared to offline) hate speech that might warrant governments and intergovernmental organisations contracting out, so to speak, the responsibility for tackling online hate speech to the very Internet companies which provide the websites and services that hate speakers utilise.
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Ullmann, Stefanie, and Marcus Tomalin. "Quarantining online hate speech: technical and ethical perspectives." Ethics and Information Technology 22, no. 1 (October 14, 2019): 69–80. http://dx.doi.org/10.1007/s10676-019-09516-z.
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Abstract In this paper we explore quarantining as a more ethical method for delimiting the spread of Hate Speech via online social media platforms. Currently, companies like Facebook, Twitter, and Google generally respond reactively to such material: offensive messages that have already been posted are reviewed by human moderators if complaints from users are received. The offensive posts are only subsequently removed if the complaints are upheld; therefore, they still cause the recipients psychological harm. In addition, this approach has frequently been criticised for delimiting freedom of expression, since it requires the service providers to elaborate and implement censorship regimes. In the last few years, an emerging generation of automatic Hate Speech detection systems has started to offer new strategies for dealing with this particular kind of offensive online material. Anticipating the future efficacy of such systems, the present article advocates an approach to online Hate Speech detection that is analogous to the quarantining of malicious computer software. If a given post is automatically classified as being harmful in a reliable manner, then it can be temporarily quarantined, and the direct recipients can receive an alert, which protects them from the harmful content in the first instance. The quarantining framework is an example of more ethical online safety technology that can be extended to the handling of Hate Speech. Crucially, it provides flexible options for obtaining a more justifiable balance between freedom of expression and appropriate censorship.
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Mateeva, Elena. "Hate speech in election campaigns." Media and Language Journal 1, no. 11 (June 14, 2022): 67–83. http://dx.doi.org/10.58894/wtwa9930.
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The democratization of the public communications language extends to the election campaigns as well. The desire to find convincing messages that set the political organization apart from its opponents has made us witness a violation of the good tone of political speech. In order to trace the language used during the July 11 parliamentary election campaigns, a review of the online publications of parties and coalitions (websites and Facebook profiles) was conducted. The research shows hostile rhetoric from almost all parties, using different methods of hate speech, incl. doublespeak, veiled hostility, presenting opponents as a public threat, etc.
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Ulfah, Aniq Noviciatie, and M. Khairul Anam. "Analisis Sentimen Hate Speech Pada Portal Berita Online Menggunakan Support Vector Machine (SVM)." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 7, no. 1 (April 15, 2020): 1–10. http://dx.doi.org/10.35957/jatisi.v7i1.196.
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Salah satu bentuk tindak kriminal yang bisa dijerat dengan undang-undang ITE adalah Hate speech. Namun saat ini netizen di Indonesia masih banyak menggunakan kata-kata Hate Speech dalam mengomentari berita di media online. Dampaknya adalah banyak netizen saat ini yang diperkarakan ke kepolisian oleh pihak yang merasa dirugikan. Hal ini terjadi karena kurangnya informasi dari netizen mengenai hate speech. Penelitian yang akan dilakukan terkait pendeteksian kata-kata yang mengadung Hate Speech pada porta berita online. Pendekatan yang digunakan untuk melakukan pendeteksian kata-kata Hate Speech menggunakan Neural Language Processing dengan menggunakan metode Support Vector Machine (SVM). Untuk mengukur tingkat keakuratan dilakukan beberapa skenario uji coba sehingga tingkat keakuratannya menjadi lebih baik. Komentar pada penelitian ini didapat pada sebuah portal berita online terpopuler di Indonesia. Algoritma SVM dapat diterapkan dalam menganalisa komentar terkait isu politik yang mengngandung Hate Speech dengan nilai akurasi yang bisa sebesar 53. 88% serta nilai Recall adalah 49,69%, Precision adalah 48,77%, Classification error adalah 46,12% dan fmeasure adalah 49.23%.. Dengan adanya penelitian yang akan dilakukan ini bisa menjadi rujukan portal berita untuk menerapkan sistem filtering sehingga kedepannya kasus-kasus mengenai Hate Speech ini dapat diminimalisir.
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Costello, Matthew, James Hawdon, and Thomas N. Ratliff. "Confronting Online Extremism." Social Science Computer Review 35, no. 5 (September 2, 2016): 587–605. http://dx.doi.org/10.1177/0894439316666272.
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Who is likely to be a target of online hate and extremism? To answer this question, we use an online survey ( N = 963) of youth and young adults recruited from a demographically balanced sample of Americans. Adapting routine activity theory, we distinguish between actor-initiated social control (i.e., self-help), other-initiated social control (i.e., collective efficacy), and guardianship and show how self-help is positively related to the likelihood of being targeted by hate. Our findings highlight how online exposure to hate materials, target suitability, and enacting social control online all influence being the target of hate. Using social networking sites and encountering hate material online have a particularly strong relationship with being targeted with victim suitability (e.g., discussing private matters online, participating in hate online) and confronting hate also influencing the likelihood of being the target of hate speech.
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Sirinyok-Dolgaryova, K. G. "HATE SPEECH IN MODERN ENGLISH-LANGUAGE ONLINE MEDIA." "Scientific notes of V. I. Vernadsky Taurida National University", Series: "Philology. Journalism" 3, no. 4 (2021): 219–24. http://dx.doi.org/10.32838/2710-4656/2021.4-3/36.
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Kim, Sooah, Minjeong Kim, Donghoo Lee, and Sungil Hong. "Regulatory Issues and Alternatives of Online Hate Speech." Korean Journal of Communication & Information 101 (June 30, 2020): 203–30. http://dx.doi.org/10.46407/kjci.2020.06.101.203.
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Corazza, Michele, Stefano Menini, Elena Cabrio, Sara Tonelli, and Serena Villata. "A Multilingual Evaluation for Online Hate Speech Detection." ACM Transactions on Internet Technology 20, no. 2 (May 25, 2020): 1–22. http://dx.doi.org/10.1145/3377323.
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Vasilenko, Ekaterina. "Online hate speech in Belarus: Highlighting the topical issues." Zeitschrift für Slawistik 66, no. 4 (November 1, 2021): 558–77. http://dx.doi.org/10.1515/slaw-2021-0026.
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Summary Hate speech can be viewed as a form of socio-political conflict that might be considered an inevitable result of the shift of the historical paradigm in the former Soviet republics. In the meantime, the study of hate speech in Belarus demonstrates its relevance not only in the context of the current socio-political situation, but also because of the lack of the related research in the country. This study provides a general outline of hate speech in the Belarusian online discourse at the present time. At the beginning of the article, a brief literature review and the definition of the key terms are given. Afterwards, extralinguistic factors that influence hate speech functioning within the discourse community are described. Most attention is paid to the linguistic analysis of the legal documents of the Republic of Belarus as compared to those of other countries. Then, based on the analysis of the Internet users’ comments to online news, the most topical issues are determined and some observations on labeling as a move aimed at creating an image of a social group are provided.
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Yin, Wenjie, and Arkaitz Zubiaga. "Towards generalisable hate speech detection: a review on obstacles and solutions." PeerJ Computer Science 7 (June 17, 2021): e598. http://dx.doi.org/10.7717/peerj-cs.598.
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Hate speech is one type of harmful online content which directly attacks or promotes hate towards a group or an individual member based on their actual or perceived aspects of identity, such as ethnicity, religion, and sexual orientation. With online hate speech on the rise, its automatic detection as a natural language processing task is gaining increasing interest. However, it is only recently that it has been shown that existing models generalise poorly to unseen data. This survey paper attempts to summarise how generalisable existing hate speech detection models are and the reasons why hate speech models struggle to generalise, sums up existing attempts at addressing the main obstacles, and then proposes directions of future research to improve generalisation in hate speech detection.
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Choi, Moon Young, Heui Jae Choi, Dong Kwon Lee, and Jong Bok Byun. "Big Data Analysis of Online Gender-Based Hate Speech: With a focus on comments on web portal news articles." Taegu Science University Defense Security Institute 6, no. 4 (August 31, 2022): 13–31. http://dx.doi.org/10.37181/jscs.2022.6.4.013.
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Current studies on online gender-based hate speech have focused on legal regulations and countermeasures. In this study, we analyzed, using a data mining technique, comments on news articles about gender issues published on web portals. Our analysis of articles published by various newspaper companies on Naver and Daum revealed that hate speech in comments was significantly higher for articles reporting on specific events related to gender issues than for general articles on gender issues. This trend is consistent for articles across all news companies, regardless of political orientation. However, web portals have the power to regulate gender-based hate speech on their sites. Daum operates a reporting system for discrimination and hate speech and has significantly fewer hate speech postings compared to Naver, which lacks such a system. This study empirically analyzed the changes in the quantity of gender-based hate speech and found that web portals, commonly classified as bystanders or gatekeepers, can play a functional role in reducing online gender-based hate speech.
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Ștefăniță, Oana, and Diana-Maria Buf. "Hate Speech in Social Media and Its Effects on the LGBT Community: A Review of the Current Research." Romanian Journal of Communication and Public Relations 23, no. 1 (April 1, 2021): 47. http://dx.doi.org/10.21018/rjcpr.2021.1.322.
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Hate speech on social media is a real problem with real consequences. Despite the constant efforts of social media platforms to moderate, flag, and ban hate posts, there is still a vast amount of hateful content flooding them. Hate speech, in general, and offensive material online, in particular, are not easy to define and may include a wide spectre of expression. To thoroughly account for the nature and intensity of the effects of hate speech in social media requires to distinguish between various shades of hate speech targeting different groups and their subsequent effects. This paper seeks to review the literature on the psychological effects of online hate speech on the LGBT community and to highlight the strong negative impact of this phenomenon. The paper aims to contribute to the field by examining the propagation and the effects of derogatory language and hate speech based on sexual orientation.
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Rangkuti, Rahmadsyah, Andi Pratama, and Zulfan Zulfan. "HATE SPEECH ACTS: A CASE IN BATU BARA." Language Literacy: Journal of Linguistics, Literature, and Language Teaching 3, no. 2 (December 19, 2019): 225–33. http://dx.doi.org/10.30743/ll.v3i1.1998.
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Hate speech acts that occur in the online realm expressed with words of prejudice and negative feelings are far more dangerous than in the offline realm. Hate speech is a new area in the study of illocutionary speech acts. This new area of speech acts becomes more interesting because every hate speech has various meanings or illocutionary forces based on speaker’s intention. This study aims to analyse the classifications and aims of illocutionary acts and illocutionary forces of hate speech contained in two face book group accounts related to Batu Bara district’s local election. The research method is descriptive qualitative. The data of this research are thirteen utterances/speeches of face book users in Batu Bara district’s local election group account. Data were collected using the documentation method with the help of referring technique. This method is used to observe the expression of the face book users’ hatred on issues related to social, cultural and political background on each candidate. Thirteen utterances analyzed are classified into assertive, directive and expressive and have illocutionary forces namely insulting, inciting and discriminating. This study indicates that hate speech can be identified linguistically.
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Sajlan, Devanshu. "Hate Speech against Dalits on Social Media: Would a Penny Sparrow be Prosecuted in India for Online Hate Speech?" CASTE / A Global Journal on Social Exclusion 2, no. 1 (May 16, 2021): 77–96. http://dx.doi.org/10.26812/caste.v2i1.260.
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This article analyzes the Indian hate speech law from the perspective of social media. Recent research shows extensive use of caste-based hate speech on Facebook, including derogatory references to caste-based occupations such as manual scavenging. This article attempts to examine whether the Scheduled castes / Scheduled Tribes (SC / ST) Prevention of Atrocities Act is equipped to deal with online hate speech against Dalits. The jurisprudence around the applicability of Atrocities Act to caste-based hate speech has been analyzed. After the said analysis, the applicability of ‘International Convention on the Elimination of All Forms of Racial Discrimination (ICERD)’ to caste- based discrimination has been studied. Thereafter, the standard of proof for prosecuting hate speech under Indian domestic law has been compared with ICERD to analyze whether Indian domestic law is in compliance with international standards. The article further analyzes whether caste-based hate speech ought to be regulated only when there is incitement to violence or hatred, or it can also be regulated when it violates the right to dignity of Dalits. At the same time, the article also briefly examines whether such prosecution would be in violation of global free-speech standards.
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Archutowski, Natalie. "Predicting the Escalation to Violence of Online Hate Groups." Journal of Intelligence, Conflict, and Warfare 4, no. 3 (February 18, 2022): 212–17. http://dx.doi.org/10.21810/jicw.v4i3.4191.
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On November 24, 2021, Natalie Archutowski presented on the topic of Predicting the Escalation to Violence of Online Hate Groups at the 2021 CASIS West Coast Security Conference. Primary topics of discussion included influencers on right wing websites, the effects of algorithms using traditional hate speech terms, the correlation between softly violent culturally nuanced hate speech and kinetic violence, and models used to help determine the presence of soft violence and the likelihood of escalation. The presentation was followed by a question and answer period and a breakout room session with questions from the audience and CASIS Vancouver executives.
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Ghozali, Imam, Kelly Rossa Sungkono, Riyanarto Sarno, and Rachmad Abdullah. "Synonym based feature expansion for Indonesian hate speech detection." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (February 1, 2023): 1105. http://dx.doi.org/10.11591/ijece.v13i1.pp1105-1112.
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Online hate speech is one of the negative impacts of internet-based social media development. Hate speech occurs due to a lack of public understanding of criticism and hate speech. The Indonesian government has regulations regarding hate speech, and most of the existing research about hate speech only focuses on feature extraction and classification methods. Therefore, this paper proposes methods to identify hate speech before a crime occurs. This paper presents an approach to detect hate speech by expanding synonyms in word embedding and shows the classification comparison result between Word2Vec and FastText with bidirectional long short-term memory which are processed using synonym expanding process and without it. The goal is to classify hate speech and non-hate speech. The best accuracy result without the synonym expanding process is 0.90, and the expanding synonym process is 0.93.
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Millar, Sharon, Rasmus Nielsen, Anna Vibeke Lindø, and Klaus Geyer. "The use of hyperlinking as evidential practice in Danish online hate speech." Pragmatics and Society 11, no. 2 (July 13, 2020): 241–61. http://dx.doi.org/10.1075/ps.18070.mil.
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Abstract Using data from readers’ comments to news articles from a national Danish newspaper, the article addresses the nature and function of hyperlinks as evidential practice in relation to xenophobic hate speech. Hyperlinks refer to the use of URL addresses to link to websites; hate speech is understood broadly as stigmatising discourse. Adopting a discursive approach to evidentiality that accounts for a range of phenomena including source of knowledge, participant roles, epistemic stance and interactional force, hate speech related hyperlinks and their evidential functions were identified. While not prevalent in number, hyperlinks serve to legitimise negative stances towards minority groups but also support counter speech targeting prejudicial views. Links can be used as part of processes of metaphorical shift and sarcasm as well as to provoke hate speech in comment threads. As URL addresses are frequently textual, they can have evidential functions independent of the material that they link to.
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Pasta, Stefano. "Hate Speech Research: Algorithmic and Qualitative Evaluations. A Case Study of Anti-Gypsy Hate on Twitter." Research on Education and Media 15, no. 1 (January 28, 2023): 130–39. http://dx.doi.org/10.2478/rem-2023-0017.
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Abstract Hate speech may be the research focus of the interdisciplinary field of hate studies, but it is also a difficult phenomenon to define. Internationally, there are several detection studies on automatically detecting hate speech. They can be grouped according to two approaches: the first includes searching using only machine learning methods, while the second includes studies that combine automatic searching with human classification. The case study on anti-Gypsy hate in Italian on Twitter in the second half of 2020 falls into the second category, and its methods are outlined here. Based on the results (annotation as ‘hate’/‘non-hate’, identification of forms of rhetoric and anti-Gypsyism), the researchers propose classifying online content according to seven indicators called the ‘spectrum of online hate’.
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Sánchez-Holgado, Patricia, Javier J. Amores, and David Blanco-Herrero. "Online Hate Speech and Immigration Acceptance: A Study of Spanish Provinces." Social Sciences 11, no. 11 (November 14, 2022): 515. http://dx.doi.org/10.3390/socsci11110515.
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Online hate speech against migrants and refugees poses a grave challenge for coexistence and democracy. However, it also offers an opportunity to measure social acceptance towards this group. Using the Intergroup Contact and the Mediated Intergroup Contact Theory, and an already validated methodology, this article seeks to validate whether the use of hate speech as a predictor of social acceptance is valid at a provincial level in Spain. Contrasting 97,710 tweets about migrants and refugees with secondary data from public Spanish institutions about acceptance of immigration and foreign population, no correlation was observed, rejecting the main hypotheses, and hinting that the application of this approach might not be recommended for smaller entities, such as provinces (NUTS 3). However, the study offers descriptive data about racist hate speech spread on Twitter in Spain, and also discusses the need for more studies using big data to increase knowledge about online hate speech against migrants and refugees.
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Jääskeläinen, Tuula. "Countering hate speech through arts and arts education." Policy Futures in Education 18, no. 3 (May 13, 2019): 344–57. http://dx.doi.org/10.1177/1478210319848953.
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Hate speech has become a growing topic of discussion and debate on a global scale, especially as advances in the internet transform communication on many levels. Among scholars, hate speech has been defined as any form of expression – for example by means of speech, images, videos or online activity – that has the capacity to increase hatred against a person or people because of a characteristic they share or a group to which they belong. In order to maintain the integrity of a functioning democracy, it is important to identify the best balance between allowing freedom of expression and protecting other human rights by countering hate speech. In addition to strengthening the legal framework to address the cases when hate speech can be considered criminal, and developing automated monitoring of online systems to prevent the spreading of cyberhate, counter narratives can be utilized by the targets of hate speech and their communities to create campaigns against hate speech. The employment of artists’ expression and arts education have great potential for creating different counter narratives to challenge one-sided narratives and hate speakers’ simplified generalizations. Because hate speech is not an easy issue to address in schools, clear research evidence, concrete guidelines and practical examples can help teachers to contribute, along with their students, in combating it. A great body of evidence supporting the beneficial social impacts of the arts and culture fields is already available, but much more research, backed by sufficient resources, is needed to evaluate the impact and effectiveness of intervention strategies in countering hate speech through arts education.
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Guo, Lei, and Brett G. Johnson. "Third-Person Effect and Hate Speech Censorship on Facebook." Social Media + Society 6, no. 2 (April 2020): 205630512092300. http://dx.doi.org/10.1177/2056305120923003.
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By recruiting 368 US university students, this study adopted an online posttest-only between-subjects experiment to analyze the impact of several types of hate speech on their attitudes toward hate speech censorship. Results showed that students tended to think the influence of hate speech on others was greater than on themselves. Their perception of such messages’ effect on themselves was a significant indicator of supportive attitudes toward hate speech censorship and of their willingness to flag hateful messages.
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Tong, Stephanie Tom, and David C. DeAndrea. "The Effects of Observer Expectations on Judgments of Anti-Asian Hate Tweets and Online Activism Response." Social Media + Society 9, no. 1 (January 2023): 205630512311572. http://dx.doi.org/10.1177/20563051231157299.
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The rise of racial hate speech on social media has raised critical questions for scholars to explore. It is necessary to understand how outside observers passively evaluate (a) online racial hate speech posts on social media and (b) whether those evaluations are related to observers’ subsequent behavior. This study explored how observers evaluate acts of majority-on-minority and minority-on-minority anti-Asian hate tweets on Twitter. In an experiment ( n = 196) informed by expectancy violations theory, we tested how White observers evaluated anti-Asian tweets ostensibly posted by either a White or Black source. Analysis revealed a moderated-mediation pathway in which observers’ political partisanship (Democrat/Republican) affected how they judged the ethnic prototypicality of White and Black sources of racial hate speech; these source prototypicality judgments were in turn associated with observers’ judgments of tweet offensiveness and self-reported intentions to engage in online activism (i.e., signing an online petition). These results contribute to our understanding of outside observers’ differential expectancies regarding online hate speech, and how those expectancies can affect perceptions of and reactions to acts of racism.
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Mathias, Jerico, and Rosamine Blessica. "Hate Speech and the Freedom Discourse." Indonesia Media Law Review 1, no. 1 (January 31, 2022): 1–22. http://dx.doi.org/10.15294/imrev.v1i1.56673.
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Hate speech accompanies intellectual freedom in new media. In the context of Indonesia, this phenomenon is very important during a political event such as legislative elections, presidential election, or elections of regional head. Since the 2014 presidential election, the term 'haters' was widely known, titled people with golden messages hateful to certain people or groups. Especially for netizens (youth users) - the Y and Z generation, the practice of communication with these hate messages should receive special attention. In addition to the heir of the nation, this is what coloring cyberspace now. They are native to the digital world (digital native). They are aware of the right to speak and express but understand that the online realm is the public domain inherent in normative responsibility. This paper reviews efforts to send hate messages through hate speech legislation (Hate Speech) laws and how ITE laws against hate speech acts.
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Calderón, Fernando H., Namrita Balani, Jherez Taylor, Melvyn Peignon, Yen-Hao Huang, and Yi-Shin Chen. "Linguistic Patterns for Code Word Resilient Hate Speech Identification." Sensors 21, no. 23 (November 25, 2021): 7859. http://dx.doi.org/10.3390/s21237859.
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The permanent transition to online activity has brought with it a surge in hate speech discourse. This has prompted increased calls for automatic detection methods, most of which currently rely on a dictionary of hate speech words, and supervised classification. This approach often falls short when dealing with newer words and phrases produced by online extremist communities. These code words are used with the aim of evading automatic detection by systems. Code words are frequently used and have benign meanings in regular discourse, for instance, “skypes, googles, bing, yahoos” are all examples of words that have a hidden hate speech meaning. Such overlap presents a challenge to the traditional keyword approach of collecting data that is specific to hate speech. In this work, we first introduced a word embedding model that learns the hidden hate speech meaning of words. With this insight on code words, we developed a classifier that leverages linguistic patterns to reduce the impact of individual words. The proposed method was evaluated across three different datasets to test its generalizability. The empirical results show that the linguistic patterns approach outperforms the baselines and enables further analysis on hate speech expressions.
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Šori, Iztok, and Vasja Vehovar. "Reported User-Generated Online Hate Speech: The ‘Ecosystem’, Frames, and Ideologies." Social Sciences 11, no. 8 (August 19, 2022): 375. http://dx.doi.org/10.3390/socsci11080375.
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The spread of hate speech challenges the health of democracy and media systems in contemporary societies. This study aims to contribute to a better understanding of user-generated online hate speech reported by Internet users to national monitoring organizations, in particular its ‘ecosystem‘, discursive elements, and links to political discourses. First, we analyzed the main characteristics of the reported statements (source, removal rate, and targets) to reveal the media and political context of reported user-generated online hate speech. Next, we focused on hate speech statements against migrants and analyzed their discursive elements with the method of critical frame analysis (frames, actors, metaphors, and references) to understand the corresponding discourse. The main discursive feature of these statements is the prognosis, which calls for death and violence, so we could label this communication as ‘executive speech.’ Other key features are references to weapons and Nazi crimes from WWII, indicating the authors’ extreme-right ideological convictions, and the metaphors, employed to provoke disgust from migrants, present them as culturally inferior and raise fears about their supposed violent behavior. The corresponding diagnoses frame migrants as a threat in a similar way to populist political discourses of othering and complement these in providing ‘final’ solutions in prognoses.
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Markogiannaki, Maria, Leukothea Biniari, Eleni Panagouli, Loretta Thomaidis, Theodoros N. Sergentanis, Flora Bacopoulou, Thomas Babalis, et al. "Adolescent Perspectives About Online Hate Speech: Qualitative Analysis in the SELMA Project." Acta Medica Academica 50, no. 2 (November 21, 2021): 264. http://dx.doi.org/10.5644/ama2006-124.342.
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<p><strong>Objective</strong>. This paper aims to study the views, perceptions and representations of online hate speech among adolescents in the Greek cohort of the SELMA Project.</p><p><strong>Methods</strong>. Qualitative research was conducted in focus groups of 36 Greek adolescents and the data were processed through thematic analysis method.</p><p><strong>Results</strong>. The majority was unfamiliar with the term “hate speech” and confused it with cyberbullying. The target characteristics of hate, ethnicity, race, gender, religion, physical weakness, disability, sexual orientation, and appearance emerged. Regarding people involved in hate speech, perpetrators in both hate speech and bullying were described to share common characteristics. The emphasis was placed on the victims’ resilience, as well as their socialization, as protective behaviors. Participants stressed the value of the right to freedom of speech, although there was no agreement on its limits. Additionally, it was highlighted that awareness of what is right and wrong is mostly taught by parents, while the role of education was also important. An important finding was that the majority of teenagers were optimistic, supporting the belief that it is possible to find a realistic solution.</p><p><strong>Conclusion</strong>. The findings support the need for prevention strategies in the school environment, so that adolescents will be able to recognize and potentially combat hate speech in the online and offline worlds.</p>
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Castaño-Pulgarín, Sergio Andrés, Natalia Suárez-Betancur, Luz Magnolia Tilano Vega, and Harvey Mauricio Herrera López. "Internet, social media and online hate speech. Systematic review." Aggression and Violent Behavior 58 (May 2021): 101608. http://dx.doi.org/10.1016/j.avb.2021.101608.
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Woods, Freya A., and Janet B. Ruscher. "Viral sticks, virtual stones: addressing anonymous hate speech online." Patterns of Prejudice 55, no. 3 (May 27, 2021): 265–89. http://dx.doi.org/10.1080/0031322x.2021.1968586.
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