Analysis Of Hate Speech Research Articles

Sentiment analysis of hate speech as an information tool to prevent riots and environmental damage

Twitter is currently one of the most popular social media in the world. Indonesia ranked in 8th the most Twitter users from all over the world with the 10.65 million users. President of the Republic of Indonesia, Joko Widodo, was ranked 8th leader with the most followers on Twitter, with 11 million users. Everyone can express or give an opinion on something or what they thought through social media including create or spreading the hate speech. One result of this hate speech can lead to mass demonstrations which can result in environmental destruction. Our research focused on sentiment analysis of hate speech towards Indonesian president by comparing the performance between Random Forest algorithm and Support Vector Machine algorithm to prevent the negative result of hate speech that can be happen in the future. This research obtained 550 tweets and labelled manually whether it is categorized as a hate speech or not and divided into each of 275 data for positive and negative sentiments. Random Forest classifier has the best performance by combining gini criterion with the number of trees 128 with the result of the accuracy score is 76.7%, precision score 82.7%, recall score 64%, and F1 score 73.3%. Support Vector Machine classifier has the best performance by combining the linear kernel type and set the C parameter to 100 with the result of the accuracy score at 74.7%, precision score 100%, recall score 49.3%, and F1 score 66.1%. Random Forest classifier performs its best in scoring F1 score, accuracy, and recall while Support Vector Machine classifier performs its best in scoring precision. Based on the results, Random Forest classifier for hate speech detection can be applied for hate speech detection to prevent damaging the environment as it shows better score on accuracy and F1 score than Support Vector Machine Classifier.

An Analysis of Hate Speech among Armenian Facebook Users

Social media networking websites have become platforms where users can not only share their photos, moments of happiness, success stories and best practices, but can also voice their criticism, discontent and negative emotions. It is interesting to follow how something that starts as a mere disagreement or conflict over clashing interests or values can develop into a hateful exchange on Facebook that targets social media users based on their gender, religious belonging, ethnicity, sexual orientation, political convictions etc. The present research explores how hateful posts and comments can start among Facebook users, and studies the language means employed in their design. The factual material was retrieved from more than ten open Facebook pages managed by popular Armenian figures, such as media experts, journalists, politicians and bloggers, in the period 2018–2020. The analysis of hate speech samples extracted from these sources shows that hate speech can find its explicit and implicit reflection in the online communication of Armenian Facebook users, and can be characterised by contextual markers such as invisibility, incitement to violence, invectiveness and immediacy. The language analysis of the posts and comments comprising hate speech has helped to identify language features of hateful comments including informal tone, use of passive voice, abusive and derogatory words, rhetorical or indirectly formed questions, generalisations and labelling.

From Euphemism to Verbal Aggression in British and Armenian Cultures


 The topic of the present article concerns verbal aggression and focusses on the verbal expression of the emotional mind; specifically, the expression of negative feelings, emotions and attitudes. Since computer-mediated communication is widely used to shape and reshape public opinion, the analysis of hate speech on the material of internet discourse may shed light on the manipulative communicative tactics that are used in online media and social networking sites to spread hostility and negativity globally. Hence, the examination of the language strategies and tactics that are used to formulate hate speech becomes essential in communicatively oriented linguistic studies.
 
 
 The present article provides a comparative analysis of manifestations of hate speech and euphemisms in Armenian and British online media outlets and social sites targeted towards people's sexual orientation. The aim of the paper is to show the close connection between hate speech and culture. The research, which embarks on two basically different cultures – British and Armenian – is carried out within the framework of cross-cultural pragmatics and discourse analysis. A qualitative research method is applied to analyse samples of hate speech. Social sites and online media outlets were searched through search engines, using certain keywords (LGBT, sexual minorities, etc.). For the purpose of the study, language resources from English and Armenian – words, expressions, constructions, speech acts expressing hostile attitudes towards sexual orientation – have been picked out and analysed.

Form of Hate Speech Comments on Najwa Shihab Youtube Channels in The General Election Campaign of President and Vice President of The Republic of Indonesia 2019

Emerging and spreading hate speech online was a growing phenomenon in social media on youtube. Najwa Shihab was a youtube channel that contains shows and comments on political issues in Indonesia, one of them was the 2019 presidential election campaign. The form of hate speech in comments in the Najwa Shihab Channels was forming grammatical construction and construction of the meaning of one hate speech with other utterances. The purpose of this study was to analyze the illocutionary speech acts on hate speech and to analyze hate speech based on the rule of law in Indonesia. The analysis resulted in hate speech on the Najwa Shihab youtube channel audience comments in the General Election campaign in the discourse of the President and Vice President of the Republic of Indonesia in 2019. The approach that used in this study was a theoretical approach, namely a forensic linguistic approach by utilizing pragmatics for data analysis, and a methodological approach, namely a qualitative descriptive approach. The data on hate speech that was analyzed was a fragment of the audience's comments on two programs, namely Mata Najwa and Catatan Najwa. The results showed that there were nine forms of hate speech. Two forms of hate speech were considered to be the style of speech that was widely used by the public in delivering comments on social media. The forms of the speech were "Form of Hate Speech, Assertive Speech - Insult" and "Form of Hate Speech, Assertive Speech - Defamation". The existence of this form of speech can be a reference for the community to process opinions first before conveying it on social media. It's legally can be used as an offense in cases of hate speech.

Detection of Hate Speech in COVID-19-Related Tweets in the Arab Region: Deep Learning and Topic Modeling Approach.

BackgroundThe massive scale of social media platforms requires an automatic solution for detecting hate speech. These automatic solutions will help reduce the need for manual analysis of content. Most previous literature has cast the hate speech detection problem as a supervised text classification task using classical machine learning methods or, more recently, deep learning methods. However, work investigating this problem in Arabic cyberspace is still limited compared to the published work on English text.ObjectiveThis study aims to identify hate speech related to the COVID-19 pandemic posted by Twitter users in the Arab region and to discover the main issues discussed in tweets containing hate speech.MethodsWe used the ArCOV-19 dataset, an ongoing collection of Arabic tweets related to COVID-19, starting from January 27, 2020. Tweets were analyzed for hate speech using a pretrained convolutional neural network (CNN) model; each tweet was given a score between 0 and 1, with 1 being the most hateful text. We also used nonnegative matrix factorization to discover the main issues and topics discussed in hate tweets.ResultsThe analysis of hate speech in Twitter data in the Arab region identified that the number of non–hate tweets greatly exceeded the number of hate tweets, where the percentage of hate tweets among COVID-19 related tweets was 3.2% (11,743/547,554). The analysis also revealed that the majority of hate tweets (8385/11,743, 71.4%) contained a low level of hate based on the score provided by the CNN. This study identified Saudi Arabia as the Arab country from which the most COVID-19 hate tweets originated during the pandemic. Furthermore, we showed that the largest number of hate tweets appeared during the time period of March 1-30, 2020, representing 51.9% of all hate tweets (6095/11,743). Contrary to what was anticipated, in the Arab region, it was found that the spread of COVID-19–related hate speech on Twitter was weakly related with the dissemination of the pandemic based on the Pearson correlation coefficient (r=0.1982, P=.50). The study also identified the commonly discussed topics in hate tweets during the pandemic. Analysis of the 7 extracted topics showed that 6 of the 7 identified topics were related to hate speech against China and Iran. Arab users also discussed topics related to political conflicts in the Arab region during the COVID-19 pandemic.ConclusionsThe COVID-19 pandemic poses serious public health challenges to nations worldwide. During the COVID-19 pandemic, frequent use of social media can contribute to the spread of hate speech. Hate speech on the web can have a negative impact on society, and hate speech may have a direct correlation with real hate crimes, which increases the threat associated with being targeted by hate speech and abusive language. This study is the first to analyze hate speech in the context of Arabic COVID-19–related tweets in the Arab region.

Anti-Discrimination Act and the Constitution — With Some Analysis of Hate Speech —

Anti-Discrimination Act and the Constitution — With Some Analysis of Hate Speech —

Hate begets Hate

With the ongoing debate on 'freedom of speech' vs. 'hate speech,' there is an urgent need to carefully understand the consequences of the inevitable culmination of the two, i.e., 'freedom of hate speech' over time. An ideal scenario to understand this would be to observe the effects of hate speech in an (almost) unrestricted environment. Hence, we perform the first temporal analysis of hate speech on Gab.com, a social media site with very loose moderation policy. We first generate temporal snapshots of Gab from millions of posts and users. Using these temporal snapshots, we compute an activity vector based on DeGroot model to identify hateful users. The amount of hate speech in Gab is steadily increasing and the new users are becoming hateful at an increased and faster rate. Further, our analysis analysis reveals that the hate users are occupying the prominent positions in the Gab network. Also, the language used by the community as a whole seem to correlate more with that of the hateful users as compared to the non-hateful ones. We discuss how, many crucial design questions in CSCW open up from our work.

Hate Speech: A Systematized Review

This review focuses on papers on Hate Speech, particularly in legal and communication studies indexed in Web of Science. It analyzes output published in English and in Spanish as well as surveys the predominant disciplines in which these studies are written, their trend over time, by country, and type of document. This research is extended to determine the debates, lines of work of greatest interest, and the theories elaborated. The legal literature is intended to define hate speech and hate crime for the purposes of applying criminal sanctions. From the communication standpoint, the analysis of hate speech in the media is key to understanding the type of message used, its emitter, the way in which the message rallies supporters, and how they interpret the message. Spanish studies mostly fall within the legal area, in which they focus on cases of insult directed at the Catholic religion. We discuss the importance of interdisciplinarity and transversality and propose a mapping of hate speech that lends itself to comparisons between countries to assess measures to counteract their effects.

Stigmatization in social media: Documenting and analyzing hate speech for COVID-19 on Twitter.

As the COVID‐19 pandemic has unfolded, Hate Speech on social media about China and Chinese people has encouraged social stigmatization. For the historical and humanistic purposes, this history‐in‐the‐making needs to be archived and analyzed. Using the query “china+and+coronavirus” to scrape from the Twitter API, we have obtained 3,457,402 key tweets about China relating to COVID‐19. In this archive, in which about 40% of the tweets are from the U.S., we identify 25,467 Hate Speech occurrences and analyze them according to lexicon‐based emotions and demographics using machine learning and network methods. The results indicate that there are substantial associations between the amount of Hate Speech and demonstrations of sentiments, and state demographics factors. Sentiments of surprise and fear associated with poverty and unemployment rates are prominent. This digital archive and the related analyses are not simply historical, therefore. They play vital roles in raising public awareness and mitigating future crises. Consequently, we regard our research as a pilot study in methods of analysis that might be used by other researchers in various fields.

The Subversive Tendencies of Religious Majoritarianism: The Rubric for Hate Crimes in India

The idyllic perspective of secularism is interwoven in the fabric of the omnipotent law that wields supremacy over the territorial confines of the Indian State i.e. the Indian Constitution. The Constitution has further been adequately supplemented by several legislative measures intended to act as a guarantee for the exiguous civil right of freedom of religion, irrespective of theological affiliation. However, despite the intentions behind these enactments, there happens to be a glaring inadequacy of embargo on detractors of religious freedom. The common phenomenon in contemporary India is to be puritanically pejorative towards sections of society that constitute the minority groups in an effort to erase their identity. This execrable tendency finds its expression in the weaponization of hate advocated under the pretentious guise of philanthropic populism. Deleterious actions fueled by the vitriol of hate often utilise speech as an effective tool for gaslighting the vulnerable, impressionable public and disrupt the status quo of prevalent societal norms. Another disparaging scenario in the present context is the erroneous retributive punishments for miscreants whose criminal misdemeanours originate in the putrid vileness of hate. By devolving into hate crimes motivated by religious identity, this paper examines the evolutionary trajectory, contributing factors. Moreover, by dissecting the existing legal structure that has permitted the pervasive persistence of hate crimes, this paper attempts to provide a microcosmic analysis of hate speech and hate crimes insofar as their ability to permeate the existing rungs of Indian society is concerned.

Words that Hurt (1): Normative and Institutional Considerations in the Regulation of Hate Speech in Europe

Europe is experiencing at present intense dilemmas in regulating hate speech and online harassment. Free speech exercise can be offensive and even contribute to a climate of prejudice and discrimination against minorities. Often, the media exacerbate the tendency by reporting negatively about minorities. The first working paper on this topic engages with the normative dimensions of the balance between the need to control and limit incitement to violence in reconciliation with the fundamental right to freedom of expression. Three distinct aspects of hate speech are covered: the first relates to the role of freedom of expression as a tool of inclusiveness. With the limits of liberal tolerance being unclear, just like the definition of hate speech itself, legal actors and systems are torn between criminalising the speaker’s motive alone or in conjunction with the effects of the speech. A survey of recent related European Court of Human Rights case-law demonstrates these ambiguities. The second aspect covered looks at the challenges of the regulation of the freedom of expression in the digital age, with emphasis of the online dimensions of the phenomenon from a legal perspective. The final aspect of the paper proposes an actor-based analysis of hate speech, as it emerges from the current regulatory frameworks applied. This section deals not only with the role of the State but also with that of equality bodies, political parties and private businesses in providing more efficient networks of protection of minorities from such violent expressions of hatred.

Hate speech and identity politics. An intercultural communication perspective

Hate speech has become a key element of contemporary political discourse. It has also changed the very structure of communication. With the access to public sphere provided by social media, hate speech engages people in connective action, which allows it to construct and deconstruct collective identity. By doing this, hate speech undermines the idea of multicultural society. In order to succeed, such a society needs to engage its members in inclusive intercultural dialogue while hate speech strongly excludes all dissident voices, deepening political polarisation. This article presents an extensive analysis of hate speech from the perspective of intercultural communication. Drawing from available research and literature, the author puts forward the thesis that hate speech is a communicative phenomenon that not only disrupts intercultural dialogue, but also leads to the disintegration of multicultural society.

Linguistic violence and the “body to come”: The performativity of hate speech in J. Derrida and J. Butler

AbstractThis text analyzes the question of linguistic violence in J. Derrida and in J. Butler and shows how this question implies a consideration of the relation between language and body. The starting point is Derrida’s critic of Austin’s theory of speech acts. Through this critic Derrida establishes a relation between speech acts and writing. This connection brings to the fore the importance of the iterability as a structural feature of speech acts. The iterability becomes fundamental in Butler’s analysis of hate speech in Excitable Speech. In this book the iterability is interpreted as the ritual character of the hate speech, which reveals its political dimension. Comparing Butler and Derrida’s ideas of speech act, I try in this text to make emerge the idea of a textual body as the possibility of the resistance to the linguistic violence.

Hate Lingo: A Target-Based Linguistic Analysis of Hate Speech in Social Media

While social media empowers freedom of expression and individual voices, it also enables anti-social behavior, online harassment, cyberbullying, and hate speech. In this paper, we deepen our understanding of online hate speech by focusing on a largely neglected but crucial aspect of hate speech -- its target: either directed towards a specific person or entity, or generalized towards a group of people sharing a common protected characteristic. We perform the first linguistic and psycholinguistic analysis of these two forms of hate speech and reveal the presence of interesting markers that distinguish these types of hate speech. Our analysis reveals that Directed hate speech, in addition to being more personal and directed, is more informal, angrier, and often explicitly attacks the target (via name calling) with fewer analytic words and more words suggesting authority and influence. Generalized hate speech, on the other hand, is dominated by religious hate, is characterized by the use of lethal words such as murder, exterminate, and kill; and quantity words such as million and many. Altogether, our work provides a data-driven analysis of the nuances of online-hate speech that enables not only a deepened understanding of hate speech and its social implications, but also its detection.

DEMOKRASI VIRTUAL DAN PERANG SIBER DI MEDIA SOSIAL: PERSPEKTIF NETIZEN INDONESIA

Several hate speech which spread in social media activity aroused because of freedom of speech euphoria in a democratic nation. Those hate speech had effectively used as a negative campaign during election. This study aims to analyze hate speech and cyber war in social media. The method used is qualitative with data retrieval through in-depth interviews of netizens as opinion makers in social media, document studies and literature studies relevant to the research. The study found that cyber warfare in social media has formed two netizen polarizations. The polarization can be identified as conservative and liberal groups. Both groups are actively producing discourse, opinion, information, issues and rumors through social media. This study has implications for the change or shift of opinion leader concept on the theory of two step communication. The concept of opinion maker in the new media tradition that emerges today allows anyone anonymously to become opinion leaders.

Automatic hate speech detection in online contents using latent semantic analysis

Internet in general and social media in particular have greatly facilitated the communication, interaction and collaboration among people and different entities. As generally there is no censorship, these media sometimes are used to proliferate discourses that contain hateful messages targeting ethnic origin, religious or sexual groups, which potentially may degenerate to violent acts against individuals of such groups. Therefore, we explore the idea of building of automatic classifier that can be used for detection of hate speech in public Albanian language pages. A hate speech corpus for Albanian language is created, and then based on Support Vector Machine (SVM) approach, an automatic hate speech detection system is proposed. Such system can be used to detect and analyze hate speech in online contents over time and to enhance our knowledge on how they affect opinion creation in society.

Mapping and Analysing Hate Speech Online

The issue of hate speech is complex – it serves as an illuminative lens for researchers and practitioners, governments and citizens, as well as perpetrators and victims, to consider some of the key paradigms that underpin models of statehood and democracy. The problem becomes all the more pressing and salient in deeply divided societies that are transitioning to democracy. In such contexts and in fragile environments, political entrepreneurs are able to politicise longstanding socio-economic inequalities that mobilise deeply entrenched feeling of injustice, domination and persecution towards certain demographic and social groups, with the ultimate objective of perpetrating systematic, targeted and widespread violence. Furthermore, as access to the internet changes the ways in which individuals and groups communicate, and produces new spaces for dialogue and exchange, it also brings with it risks and concerns over the ways in which these spaces may be instrumentalised for violent ends.This working paper provides a framework through which hate speech which emerges and is disseminated online can be identified and analysed. The aims of this working paper are twofold.Firstly, it is meant to provide an introductory guide for those interested in mapping and analysing hate speech, especially as communicated through online media and in divided societies. Section 1 offers an overview of the recent debates over the definition of hate speech, both from a scholarly and legal perspective. It briefly examines how different actors, from international bodies to national legislators and online companies, have sought to regulate and counteract hate speech, and stresses the importance of balancing competing principles to advance social inclusiveness as a “public good”. Section 2 surveys different methodological tools that can be adopted to map and analyse hate speech and the trade-offs between the ability of providing a contextually grounded analysis of instances of hate speech and the possibility of processing large volumes of data. It also offers concrete case studies of projects which have innovatively analysed hate speech both online and offline.The second aim is to interrogate how a rigorous and academically informed analysis of hate speech can offer a novel terrain for engagement among different actors in divided societies, with a particular focus on Ethiopia. As it has been the case in other societies fractured across ethnic, political, and religious lines, at critical times such as before an election accusations of inciting hatred have been made by different actors to attack their opponents. The concept of hate speech advanced in these instances has tended to be boundless and to reflect more the interests and concerns of those referring to an act as hateful or able to incite hatred, rather than being based on an agreed definition. Section 3 reflects on the importance of bringing different actors around the same table, from members of the government and the opposition to bloggers supporting agendas at different ends of the political spectrum, and to engage in debates that can ultimately bound them to a shared definition of what is and what is not speech that can promote hate and violence, and to collectively recognize and develop measures to counteract it. A shared, academically rigorous and contextually grounded definition of hate speech and the mapping of instances that fall under it can help preventing governments and other political actors from politicising speech acts. Together with the analysis of how individuals are already opening spaces for dialogue on different platforms, it can offer a novel way to map where risks lie and where, on the contrary, people should be allowed to voice their opinions. In countries like Ethiopia, where calls for respecting and enforcing freedom of expression coming from external organizations, including human rights groups and donors, have tended to be ignored, this approach can open a new avenue for allowing dialogue among different forces in society, and with it a basis for a strong and vibrant democracy. The paper concludes by outlining the principles that should inform this new research agenda, aimed at mitigating ethnic, political and social fissures underlying debates on hate speech.

Introducing Two New Terms into the Literature of Hate Speech: “Hate Discourse” and “Hate Speech Act” Application of “speech act theory” into hate speech studies in the era of Web 2.0

The aim of this paper is to explain the need for a revision of the term “hate speech” in the era of Web 2.0 and to introduce two new terms into the literature of hate speech with the help of application of “speech act theory”, that is “hate discourse” and “hate speech act.” The need for the revision arises from the examination of the methodology used to analyze hate speech, which is critical discourse analysis (CDA). Even though CDA seems fairly sufficient for hate speech analysis in traditional media, it could be rather difficult to apply into the analysis of hate speech disseminated in social media because of the nature of the tremendous data found in Web 2.0. Therefore it is believed that these two new terms could be beneficial to find more practical and new ways to combat against hate speech disseminated through social media.

'You're Not Like Other' Hate Speech

Traditional semantic and pragmatic accounts of hate speech do not account for the simultaneity of certain phrases being both complimentary and incredibly offensive. My account seeks to operationalize perlocutionary-based theories of hate speech in terms of cognitive linguistics, through mental spaces theory and common ground. My thesis concerns some curious cases which show how using intention alone as a basis for interpreting the semantics and pragmatics of speech fails to account for certain speech acts which are simultaneously complimentary and offensive. My analysis shall focus on the cognitive linguistic aspects of the construction you're not like other; where X is a sociological category (Black people, Women, Muslims, etc.). This analysis will show that previous methods of semantically and pragmatically analyzing hate speech are inadequate in capturing the full contextual features and mental states of the interlocutors, and that my interpretation is more representative of reality.

“You Don't Understand, This is a New War!” Analysis of Hate Speech in News Web Sites' Comments

Because news websites' comments have become an important space of spreading hate speech, this article tries to contribute to uncovering the characteristics of Internet hate speech by combining discourse analyses of comments on Slovenian news websites with online in-depth interviews with producers of hate speech comments, researching their values, beliefs, and motives for production. Producers of hate speech use different strategies, mostly rearticulating the meaning of news items. The producers either are organized or act on their own initiative. The main motive of soldiers and believers is the mission; they share characteristics of an authoritarian personality. The key motives of the players are thrill and fun. The watchdogs are motivated by drawing attention to social injustice. The last two groups share the characteristics of a libertarian personality.