Hate Speech, Fake News, and the Moderation Problem

The internet has become an everyday tool to communicate and network with people around the globe, but its perceived anonymity, availability, and instant access have made it an environment conducive to spreading hateful content and connecting to like-minded individuals with similar hateful ideologies. Hate speech and other prejudice-motivated behavior, however, need to be considered on a continuum of victimization, and "like other social processes, [be seen as] dynamic and in a state of constant movement and change, rather than static and fixed" (Bowling, 1993, p. 238). It is a social process that is marked by multiple, repeat, and constant victimization (Bowling, 1993), with victims no longer distinguishing between specific hateful events, and rather normalizing experiences of hateful conduct "as an everyday, unwanted but routine reality of being 'different'" (Chakraborti, 2016, p. 581). Understanding hateful behavior and victimization as a process allows us to connect "low-level" incidents of hateful behavior to the more serious and life-threatening incidents at the more extreme end of the spectrum (Bowling & Phillips, 2002). The Christchurch attacks in New Zealand and their link to hateful communication on the online platform 8chan is only one such example of how online hate speech and cyberhate can escalate to "in real life" attacks, leaving the online sphere and spilling into the offline world. As per Allport's (1954) scale of prejudice, more extreme forms of prejudice-motivated violence are founded on "lower level" acts of prejudice and bias, therefore, hateful content online should not be ignored. Intervening online to interrupt or counter hateful behavior already at the lower end of the scale of prejudice becomes important; online interventions which are to be identified and synthesized through this systematic review. Allport's (1954) scale of prejudice will be the basis for this systematic review. Early on, Allport (1954) asserted that individuals with negative attitudes toward groups are likely to act out on these prejudices "somehow, somewhere" (p. 14), and that the more intense such negative attitudes are, the more hostile the action will be. Allport (1954) put forward a scale of acts of prejudice to illustrate different degrees of acting out negative attitudes, a scale that starts with antilocution (or what we call hate speech), described as explicitly expressing prejudices through negative verbal remarks to either friends or strangers (Allport, 1954). Avoidance is the next level on the scale of prejudice, with people avoiding members of certain groups, followed by discrimination, where distinctions are made between people based on prejudices, which leads to the active exclusion of members from certain groups (Allport, 1954). This level of acting on prejudices is routed in institutional or systemic prejudices, for example, in the differential treatment of people within employment or education practices, but also within the criminal justice system, or through social exclusion of certain minority group members. Physical attack is the next level on the scale of prejudice, which includes violence against members of certain groups by physically acting on negative attitudes or prejudices. The last level is extermination, which is the ultimate act of violence against members of specific groups, an expression of prejudice that systematically eradicates an entire group of people (e.g., genocide or lynchings; Allport, 1954). Allport's (1954) scale of prejudice makes it clear how hate speech/cyberhate is connected to more extreme forms of violence motivated by specific prejudices and biases, with hate speech (or antilocutions) being only the starting point on a 5-point continuum (Bilewicz & Soral, 2020). The importance of this scale of prejudice is not only that it clearly illustrates a range of different ways and intensity levels to act out prejudices, but also the "progression from verbal aggression to physical violence or, in other words, the performative potential of hate speech" (Allport, 1954; Kopytowska & Baider, 2017, p. 138). This is where interventions at the lower level of the scale of prejudices, interventions targeting hate speech/cyberhate, become important. There is no universal definition of hateful conduct online, but there is some consensus that hate speech targets disadvantaged social groups (Jacobs & Potter, 1998). Bakalis (2018) more narrowly defines cyberhate as "any use of technology to express hatred towards a person or persons because of a protected characteristic—namely race, religion, gender, sexual orientation, disability and transgender identity" (p. 87). Another definition that also points out the ambiguity and challenges involved with identifying more subtle forms of hate speech, and also making reference to the potential threat of hate speech escalating to offline violence, is that put forward by Fortuna and Nunes (2018), who analyzed various definitions of hate speech "Hate speech is language that attacks or diminishes, that incites violence or hate against groups, based on specific characteristics such as physical appearance, religion, descent, national or ethnic origin, sexual orientation, gender identity or other, and it can occur with different linguistic styles, even in subtle forms or when humour is used" (p. 5). In this systematic review, we also distinguish hate speech/cyberhate specifically from other forms of harmful online activity, such as cyber-bullying, harassment, trolling or flaming, as perpetrators of such online behavior repeatedly and systematically target specific individuals to cause upset, to seek out negative reactions, or to create discord on the internet. In contrast, hate speech/cyberhate is more general and does not necessarily target a specific individual (Al-Hassan & Al-Dossari, 2019), instead hate speech/cyberhate heavily features prejudice, bias and intolerance toward certain groups within society. With the majority of hate speech happening online, interventions that take place online are an important way to challenge prejudice and bias, potentially reaching masses of people across the globe. The unique feature of the internet is that such individual negative attitudes toward minority groups and more extreme hateful ideology can find its way onto certain platforms and can instantly connect people sharing similar prejudices. By closing the social and spatial distance, the internet creates a form of collective identity (Perry, 2000, p. 123) and can convince individuals with even the most extreme ideologies that others out there share their views (Gerstenfeld et al., 2003). In addition, the enormous frequency of hate speech/cyberhate within online environments creates a sense of normativity to hatred and the potential for acts of intergroup violence or political radicalization (Bilewicz & Soral, 2020, p. 9). It is, therefore, important to challenge this hate speech epidemic (Bilewicz & Soral, 2020), especially since hate movements have increasingly crossed into the mainstream (Perry, 2000). With hate speech/cyberhate posing a threat to the social order by violating social norms (Soral et al., 2018), perceptions of social norms as either supporting or opposing prejudice has been found to have an influence on how individuals react online (Hsueh et al., 2015). Seeing other people post prejudiced (opposed to antiprejudiced) comments online can lead to the adoption of an online group's biases and can influence an individual's own perceptions and feelings toward the targeted stigmatized group (Hsueh et al., 2015). In addition, research around desensitization also suggests that being exposed to hate speech leads to desensitization, which further leads to an increase in outgroup prejudice toward groups targeted by such speech (Soral et al., 2018). With society increasingly recognizing that it is inappropriate to express prejudices in public settings, many interventions will include some form of social norms nudging to reduce such prejudices; interventions that "nudge behavior in the desired direction" (Titley et al., 2014, p. 60). Therefore, hate speech not only affects minority group members, but also has an influence on opinions of majority group members (Soral et al., 2018), which makes strategies that can elicit change in people's prejudice-related attitudes crucial (see, e.g., Zitek & Hebl, 2007). Governments around the world face increased demand for understanding and countering hateful ideology and violent extremism both online and offline (e.g., the Christchurch Call in New Zealand). The U.S. Government's 2011 CVE Strategy highlights the importance of ongoing research and analysis, the sharing of knowledge and best practices internationally, and the countering of hateful ideologies and propaganda (see also Department of Homeland Security, 2016, 2019). The goal of this systematic review is to use an integrated and interdisciplinary approach to examine the effectiveness of online campaigns and strategies for reducing hate speech and cyberhate. The internet also provides an opportunity to reach masses of people who have been exposed to hateful content and ideology online, therefore, this systematic review will focus on online interventions addressing online hate speech and cyberhate. The specific settings where we would expect to see the online interventions deployed will be on websites, text messaging applications, and online and social media platforms including, but not limited to, Facebook, Instagram, TikTok, WhatsApp, Google, YouTube, and Snapchat. As mentioned previously, many online interventions will be based on social norm nudges to reduce online hate. These interventions aim to change people's online behavior and encourage individuals or groups to conform to established social norms. The communication of social norms can happen through establishing community standards on online platforms themselves (e.g., Facebook, Twitter, etc.), through more formal online training courses, or through anti-hate speech/anti-cyberhate campaigns teaching people to recognize hate, embrace diversity, and stand up to bias. Such prevention campaigns are designed to challenge bias and build ally behaviors by supplying people with constructive responses to combat, for example, antisemitism racism, and homophobia, as well as provide resources to help people explore and critically reflect on current events. Other interventions may add messages to hateful online comments, counter hateful content or extremist ideology, or redirect people to more credible sources. Both peers and parents have been found to foster racial consciousness and identity development, define interracial relationships and cultivate ethnic heritage and culture (Hagerman, 2016). Socialization influences how children understand their group's social position and their membership within that group by providing an understanding of racial, religious, and sexual privilege (Bowman & Howard, 1985). Socialization often reflects peers' and parents' experiences with racism, discrimination, and their ideological perspectives about race, religion, or sexuality (Umaña-Taylor & Fine, 2004). This is important because peers and parents who feel discriminated against or believe that the "other" is a threat may impart their prejudices to their children or friends, which could lead them to interpret the social world with similar discriminatory views and/or behavior. Individuals who feel socially alienated or rejected are especially vulnerable to such socialization practices as they feel that adopting these views will provide them with a sense of acceptance and belonging (Leiken, 2012). Regardless of how an individual develops certain racial, religious, or sexual biases, the online interventions under review are expected to target and reduce the production of original hateful content such as antisemitic Tweets and/or homophobic blog posts as well as the consumption of hate speech material (e.g., watching or reading hate speech videos or blogs). For example, some interventions take a rather broad messaging approach by implementing racial sensitivity and diversity training through Public Service Announcements, peer-to-peer dialogue workshops, or films that provide opportunities for youth and adults to self-reflect and learn about historical oppression, people of color, women, and the LGBTQIA+ community from credible sources. The factual understanding of diverse groups is often supplemented by experiences with people within the group. These educational programs often identify a cultural guide who is willing to introduce youth to new experiences and who can aid in processing thoughts, feelings, and behaviors. These interventions intend to dispute and contradict negative stereotypes associated with specific cultures, people, and institutions by sharing different points of view based on human rights values such as openness, respect for difference, freedom, and equality (Gomes, 2017). Moreover, such interventions tend to involve blanket bans on specific behaviors enforced through the public promotion of norms or individual sanctions enforced by moderators. Other interventions, such as the "Redirect Method," are narrower in their messaging. These interventions generate curated playlists and collections of authentic content that challenge hate speech/cyberhate narratives and propaganda (Helmus & Klein, 2018). For instance, people who are directly searching for extremist content online may be linked to videos and written content that confronts such claims. These videos are designed to be objective in appearance instead of containing material that explicitly counters extremist propaganda. The underlying goal of this type of interventions is to provide credible content that effectively undermines extremist messaging but does not overtly attack the source of propaganda. In addition to confronting hate speech narratives, these interventions provide users with links to numerous social services such as anger management training, drug and alcohol treatment, and mental health resources. Online platforms, such as Twitter and Facebook, have also started to employ a similar method, redirecting people who comment on or share "fake news" or conspiracy theories, which often are fraught with prejudicial undertones and are harmful to minority groups, to more credible content and news sources. The aforementioned interventions are designed to counter-balance these biased perceptions (e.g., unsupported claims of the Black community as criminal or the LGBTQIA+ community as pathologized) Blacks as criminals, LGBTQIA+ as pathologized) by blunting the occurrence of racist discourse and reducing the likelihood these individuals will internalize and normalize racial, religious, and/or sexual prejudices (Qian et al., 2019). Being in new situations is uncomfortable and often awakens fears and apprehensions that can block our experiential development. Acquiring information or being exposed to minority-run businesses, poverty, and writings from minority authors allows a person to understand the thoughts, hopes, fears, and aspirations of the people outside their racial perspective rather than from the perspective of the majority society (Dunham et al., 2013; Lee et al., 2017). Doing so, counters racist programming by challenging hegemonic beliefs, which can lead to the acceptance of tolerant attitudes and the reduction of hateful expressions online. Findings from the proposed review will enhance our understanding of the effectiveness of online anti-hate speech/anti-hate interventions, will help ensure that programming funds are dedicated to the most-effective efforts, and will play a critical role in helping individual programs improve the quality of service provisions. It will inform governments and policymakers of the current state of such online efforts, what works and which modes of interventions to implement, and help guide economically viable investments in nation-state security. Our search of the scholarly literature identified one review, Blaya (2019), as similar to the proposed topic. Blaya's (2019) review, however, focused on the prevalence, type, and characteristics of existing interventions for counteracting cyberhate and did not include a meta-analysis. Two other similar reviews focused on exposure to extremist online content (Hassan et al., 2018) and communication channels associated with cyber-racism (Bliuc et al., 2018). A search of the Campbell Library using key terms (hate OR radical*) returned two protocols and one review identified for further inspection to assess potential overlap. The protocols include "Psychosocial processes and intervention strategies behind Islamist deradicalization: A scoping review" by de Carvalho et al. (2019) and "Police programs that seek to increase community connectedness for reducing violent extremism behavior, attitudes and beliefs" by Mazerolle et al. (2020). A further review on a similar topic is a recently completed Campbell review (January 2020), "Counter-narratives for the prevention of violent radicalization: A systematic review of targeted interventions" by Carthy et al. (2018) at the National University of Ireland, Galway. Our proposed review is distinguished from the de Carvalho et al. (2019) review in that we are focusing on hate speech and cyberhate generally without delimiting our approach to a specific type of radicalization (e.g., Islamist). Furthermore, we are electing to complete a systematic review and meta-analysis. Likewise, the protocol by Mazerolle et al. (2020) focuses on interventions involving police officers either as initiators, recipients, or implementers of community connectedness interventions. Our review will focus specifically on any online intervention, which may or may not involve police, but police will not be the focus nor be the basis of the online intervention strategy. Judging from Carthy et al. (2018) protocol, we anticipate our review will also capture counter-narrative interventions, but will differ based on setting, timing, and scope of interventions. Specifically, we are interested in online interventions that extend beyond counter-messaging campaigns to include a broad array of interventions outlined above and extend beyond radicalization to include everyday hate and prejudice. In addition to conducting a meta-analysis, the proposed review would build on Blaya's (2019) work by expanding the population parameters to include both adolescents as well as adults. Blaya (2019) limited her search to include interventions aimed toward youth, young people, children, young adults, adolescents, children, and teenagers and did not focus on extremism. The main objective of this review is to synthesize the available evidence on the effectiveness of online interventions aimed at reducing the creation and/or consumption of online hate speech/cyberhate material. To what extent are online interventions effective in reducing online hate speech/cyberhate? How is effectiveness related to the type of online hate speech/cyberhate intervention used? How is effectiveness related to the characteristics of individuals experiencing the online hate speech/cyberhate intervention (e.g., age, gender, race/ethnicity, offense history, childhood trauma)? Both experimental and quasi-experimental quantitative studies will be included. These study designs will address research questions #1 to #3. Eligible quantitative study designs include the following: Eligible experimental designs must involve random assignment of participants to distinct treatment and control group(s). Designs that involve quasi-random assignment of participants such as alternate case assignment are also eligible and will be coded as experimental designs. All eligible quasi-experimental designs must include a comparison group of participants compared to participants in the treatment condition. Eligible studies include those that report matching procedures (individual- or group-level) and statistical procedures employed to achieve equivalency between groups. Statistical procedures may but are not limited to, analysis, and Furthermore, in of a limited quantitative evidence we will also include quasi-experimental studies with comparison groups that provide of for both groups. will also be included. Eligible include designs with a control group and designs with or without a control group than quasi-experimental designs include studies that a comparison group of participants who either to in the study or who in a but out to the of a Eligible comparison include other online interventions or in which participants not or an online Both youth and participants of any gender sexual orientation, or will be eligible for this review. The eligible youth population will be study participants with a of through The eligible population will be study participants with a of and in which only a of the is eligible for example, a study in both online and offline hate speech be not anticipate studies based on as our will be and we will take to studies that only online interventions. will of the of a study for through and be we will elicit the of a the of and studies will be these studies will be they will be and be in the and any related Blaya's (2019) of intervention strategies to the potential of eligible interventions. 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Fake News (disinformation with malicious intent) has emerged as a major social problem. To address this issue, previous studies mainly utilized single information, the news content, to detect fake news. However, using only news content in training is insufficient. Moreover, most studies did not consider the propagation aspect of fake news as a training feature. Thus, in an attempt to incorporate the ability to learn representation based on textual information and social context, this study proposed a fake news detection algorithm that thoroughly utilizes user graph in Korean fake news and dataset construction methods. In addition, a training strategy was proposed for utilizing user graph in Korean fake news detection through comparative and ablation studies. The experimental results showed that K-FANG outperformed the baseline in detecting fake news. Moreover, user engagements were found to be useful for detecting fake news even if the data contained hate speech. Finally, the validity of using stance information by expanding its class and controlling the class imbalance issues was also verified. This study provided useful implications for utilizing user information in fake news detection.

“Fake news” has become a much-used and much-hyped term in the so-called “post-truth” era that we now live in. It is also much-maligned: it is often blamed for having a disruptive impact on the outcomes of elections and referenda and for skewing democratic public debate, with the 2016 US Presidential elections and Brexit referendum often cited as examples. “Fake news” has also been flagged for fuelling propaganda and “hate speech” and even violence. “Pizzagate” is an infamous example of exceptional circumstances in which a false news story had a central role in a shooting incident. In December 2016, a man in Washington D.C. took it upon himself to “self-investigate” a story (a completely unfounded conspiracy theory) that the Hillary Clinton campaign team was running a paedophile ring from the premises of a pizzeria. Shots were fired and he was arrested and charged with assault and related offences. Given all this bad press, it is perhaps little wonder that “fake news” has become a major preoccupation for international organisations, national law- and policy-makers, the media and media actors, civil society and academia. But what exactly is “fake news” and what is all the fuss about? In addressing these questions, this column will also consider historical and contemporary perspectives on the term and its relationship with human rights.

Information and communication technologies hold immense potential to enhance our lives and societal well-being. However, digital spaces have also emerged as a fertile ground for fake news campaigns and hate speech, aggravating polarization and posing a threat to societal harmony. Despite the fact that this dark side is acknowledged in the literature, the complexity of polarization as a phenomenon coupled with the socio-technical nature of fake news necessitates a novel approach to unravel its intricacies. In light of this sophistication, the current study employs complexity theory and a configurational approach to investigate the impact of diverse disinformation campaigns and hate speech in polarizing societies across 177 countries through a cross-country investigation. The results demonstrate the definitive role of disinformation and hate speech in polarizing societies. The findings also offer a balanced perspective on internet censorship and social media monitoring as necessary evils to combat the disinformation menace and control polarization, but suggest that such efforts may lend support to a milieu of hate speech that fuels polarization. Implications for theory and practice are discussed.

Fake news is becoming a massive issue from being used to manipulate elections to spread chaos and to being darn right annoying. Fake news has become a thriving business where many companies and state agencies offer services to spread fake news deliberately to benefit their clients. Hence new techniques are required to identify and detect fake news. In this paper, we propose a novel 3-phase approach for the identification of fake news. We extracted features like WHOIS and DNS from domain information and used for the model construction. We also combine psychological factors of both the people trying to spread the fake news and the general population. We train our model on journalist labelled data and achieved more than 80% accuracy. We are also able to increase the precision and recall of fake and genuine news detection.

Down the ages and across cultures, information has occupied a very crucial space in the life of any society. Today, our world with the speed in technological advancements is characterised with easy access to the collecting, refining and distribution of information. This has left media houses especially the large ones with the burden of competing with alternative media, as media producers abuse the privilege in liberal democracies that is granted citizens as regards human rights and freedom, as the rate of disseminating false information continues to grow. This piece attempts at stating clearly information on fake news, misinformation and hate speeches as disseminated globally in the guise of media scientists, showing the means through which this end is met, especially with the easy that comes with the use of social media and in the end, showing the challenges and risks that are resultant effects of this acts.

The spread of “fake news” is a threat to the credibility of the media in the Southern African Development Community (SADC), including Eswatini (formerly Swaziland). These intentionally false stories or disinformation purporting to be news threaten the democratic role of mainstream media in creating a well-informed citizenry. There is hate speech, and disinformation directed at the royal family, the cabinet, prominent figures and the larger Swazi society. This study focuses on disinformation in the mainstream media, the Swazi Observer and the Times of Swaziland, and the strategies being adopted to combat it. The article adopts a qualitative methodological approach using in-depth interviews with journalists and qualitative content analysis of the newspapers as data-gathering methods. The study reveals that the dissemination of false information is partially a consequence of the secretive nature of Swazi society even on matters of public interest. This has resulted in people spreading false news through social media aimed at ridiculing those in authority. On the other hand, “fake news” has found its way into mainstream media as journalists use the internet and social media such as Facebook and Twitter as sources of news without verifying their authenticity due to the pressure to be the first to publish.

Conspiracy theories, fake news, hate speech, misinformation, and rumors spread in an environment of low confidence, low trust, and high bias. As the COVID-19 virus continues to spread worldwide, the lack of consensus among the scientific and political community has led to the spread of rumors and misinformation about its containment, prevention, treatment, and socio-economic ramifications. There has been unsolicited medical advice that has been put forth, such as fake homemade or herbal remedies, which has resulted in inaccurate steps to prevent the spread of the virus. There have been conspiracy theories, such as the 5G network being the cause of the virus or the virus being a biological weapon used by the Chinese. There has also been a propagation of hate speech, especially on social media, which has resulted in racially fueled attacks against Asian Americans. While some of these theories and rumors pose a small threat and have little impact, several others have destroyed property, led to racial attacks, and even individuals' death. Events like these threaten the structure of democracy and pose a threat to citizens' safety; hence, it has become important to detect and mitigate the spread of fake news and misinformation. We aim to explore natural language processing and machine learning algorithms to understand problems related to fake news and misinformation. For example, important entities, events, and story structure will be extracted automatically from various social media claims. Media bias from outlets with different ideologies and stances will be studied. To achieve this, we focus on extracting true and false claims that are made about COVID-19 on the news or social media and use these claims to identify how online users react to them. We extract the social media posts made by online users that refute or support these claims and trace the source and the political leaning of such information. The next step is to analyze whether online users prefer certain argument types (e.g., citation from an authority, anecdotal experience, study, reasoning, etc.) when they spread or refute the information. Once we understand how users react, we study how misinformation is generated and perceived over time. The question we aim to answer is if there is a distinction when misinformation is being spread or refuted.--Author's abstract

The number of digital crimes or cybercrimes today continues to increase every year, and lately a lot of it happens on social media like Instagram. The social behavior of today's people who communicate more through social media encourages the perpetrators of these digital crimes. Instagram is a social media that is often found content that contains elements of pornography, hoax news, hate speech, etc. This research is aimed at processing digital evidence of cases of the spread of hoax news on the Instagram application. This research follows the framework of the Digital Forensics Research Workshop (DFRWS) with six stages, namely identification, preservation, collection, examination, analysis, and presentation. The process of obtaining digital evidence is assisted by the application of Axiom Magnet and Cellebrite UFED. Digital evidence sought from the smartphone device of the suspected hoax news disseminator seized following the case scenario consists of 8 variables in the form of accounts, emails, images, videos, URLs, times, IP address, and location. The results of this research with the help of the application of Magnet Axiom digital proof obtained 87.5% and the Cellebrite UFED application of 68.75%. The results of this study show that Magnet Axiom has better performance than MOBILedit Forensics.

The large scale of the rise of hate speech on social media and disinformation by a large mass of social media users push governments and states to influence and take preventive measures. Today, social media is used, and in many cases through which hate speech is increasing. Given the impact on society, the spread of hate speech represents the main component that also marks an increase in different spheres. The Member States of the European Union are the basis for preventing and sanctioning hate speech online and have the Charter of Fundamental Rights of the European Union. But the fact that it results in a widespread practice for the European population: threats, violence, blackmail, disinformation, and intolerable language through social media, raised on various grounds such as race, ethnic background and sexual orientation. Disinformation, hate speech on social media and data protection, except for being regulated at the central level, as such, to deal with cases relating to these issues, Member States at state level have taken additional measures to prevent cases and to influence the reduction of victims generated by social media. The finding is marked by a sufficient number of victims through social media with multiple users of hate speech. The number of users identifying hate speech has decreased year-on-year.

(Online) hate speech appears as a growing problem in Greece and Cyprus attributed to prejudices toward specific groups, the evolution of online media, lack of awareness and of appropriate educational tools to recognize and counter it. Communication professionals and media practitioners produce hate speech content both intentionally, to gain visibility and unintentionally due to their inability to recognize it. This paper presents a study conducted simultaneously for the first time in Greece and Cyprus that explored the issue of (online) hate speech, approaching it in a socio-centric rationale as hate discourse. The issue was researched through a qualitative inquiry with semi-structured interviews and focus groups conducted in Greece and Cyprus. According to the personal and professional perceptions of the public communication experts who participated in our research, hate speech impacts predominantly vulnerable social groups, and the deficiency in legal frameworks in both countries enables rather than combats this pathogenesis. This paper contributes toward a better understanding of hate speech in the two countries and how public communication practitioners perceive and experience it.

Abstract: The increasing number of internet users has a negative impact, one of which is hate speech, so that from year to year on social media the number of hate speech continues to increase without any signs of disappearing or being resolved. Hate speech is an action that is contrary to the communication function of education as an indicator of intelligence and communication ethics. This research aims to describe forms of hate speech on social media as well as analyze hate speech in educational communication in posts by Twitter social media users. The method used in this research is descriptive qualitative. Research data was obtained through listening, taking notes, and documenting uploads and comments from Twitter account users. The results of this research show that there is hate speech on social media in the form of videos, comments, and tweets. In the form of insulting speech, defamation, incitement, provocation, spreading false news, and blasphemy. So educational communication is needed to minimize acts of hate speech by involving educational communication functions including informative functions, educational functions, persuasive functions, and expressive functions. Keywords: educational communication, hate speech

Cyber-libertarians advocate a free and unfettered cyberspace, unencumbered by regulation. Despite this idealised view, nations around the world are asserting their right to enforce individual regimes of content regulation. Universal agreement on Internet content regulation is almost impossible to obtain. Even in an area that is universally abhorrent--child pornography--the First Amendment to the United States Constitution stands as a stumbling block to effective government regulation. When the content under discussion concerns hate speech, consensus becomes more elusive. There are those who argue that freedom of speech principles preclude censorship of opinion, and that more speech is the best antidote to racist views. Others argue that hate speech silences minority opinion and is really an equality issue, which if not addressed, runs counter to International Human Rights principles. Nations such as Germany and France have prohibited hate speech on the Internet, and have brought both criminal and civil penalties against defendants. However, enforcement is fraught with difficulties, especially when the defendants are not nationals, and when the content emanates from foreign jurisdictions. The Council of Europe has recently moved to include an additional Protocol to the Convention on Cybercrime. This Protocol would cover offences of racist or xenophobic propaganda, making them subject to reciprocal enforcement provisions by Member States. Whether international efforts can succeed where a piecemeal approach has failed is yet to be seen. Although the United States and its First Amendment currently present the greatest obstacle to hate speech regulation, technological advances as well as judicial development in First Amendment jurisprudence may yet provide an avenue for regulating hate speech in cyberspace.

Hate speech is based on exclusion and devaluation of certain groups in society, which represents a systemic hierarchy. This systemic hierarchy is constructed on the basis of discourse that represents the dominant ideology and media plays an important role in the dissemination of this discourse. In this sense, hate speech is a discursive practice that serves the benefits of the dominant ideology, which is endorsed through the discourse of media. Especially, news media plays an important role in the dissemination of hate speech because news is considered as the representation of real life. This study aims to analyze online health news in terms of hate speech against HIV/AIDS and understand how HIV positive people perceive this hate speech. For examining online news, critical discourse analysis method is adopted; and in-depth interviews are carried out with ten HIV positive people. Findings of the analysis of in-depth interviews are in accordance with the findings of critical discourse analysis, as HIV positive people claim that online news promotes and popularizes prejudices, stigmatization and discrimination against them and that online news’s content involves misrepresentations, misinformation, and incorrect use of terminology. Even though hate speech encompasses all types of expressions that promote, popularize, defend or justify discriminatory, intimidating, disapproving and prejudicial attitudes, HIV positive people do not describe this as hate speech, which points to the fact that hate speech is internalized and justified by its victims.

The Battle against Hate Speech and Freedom of Expression Online