Editorial: Understanding malicious behaviors on digital platforms.

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. The intervention is the of responses to hate speech/cyberhate, which includes the countering of violent extremism and to address online interventions that are eligible range from hateful content online specific (e.g., of social media to to online hate using targeted strategies (e.g., through hateful of studies focusing on online include the and of online and content online content and & 2018), hateful online comments to comments et al., 2018), and to users out of online are also interested in interventions such as the of 8chan this online platform linked to "in real life" attacks in New Zealand and the and interventions that further hateful online content and radicalization similar events. hateful content online such has up speech as well as around online users and hateful groups on to other online to hateful content online using targeted strategies therefore, been as an effective online include using the from & 2020), the use of to online responses to in online where hate speech has been (Qian et al., 2019), and redirecting online users to videos for example, Our systematic review will include a range of online interventions, many of which have only recently Two other strategies identified by Blaya (2019) are the and of hate speech/cyberhate using technology as well as the creation of online and These interventions include online counter-narrative the and/or use of online counter online interventions, online training, and online narrowly to address extremist ideologies and hate speech that incites targeted violence and In such interventions seek to or the occurrence of violent extremism or the of hate speech and extremist by channels and opportunities to such groups. 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By we to the production and of original hateful content such as antisemitic racist and/or homophobic blog The consumption of hate speech material may include or being a of a hate watching or reading hate speech videos or being a target of online hate speech/cyberhate, or hate speech material. of include and of study participants such as and attitudes toward hate Eligible studies must report a or (or to be included. 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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.

Putting the Toothpaste Back in the Tube: Against Online Hate Speech.

Social media sites such as Twitter and Facebook have connected billions of people and given the opportunity to the users to share their ideas and opinions instantly. That being said, there are several negative consequences as well such as online harassment, trolling, cyber-bullying, fake news, and hate speech. Out of these, hate speech presents a unique challenge as it is deeply engraved into our society and is often linked with offline violence. Social media platforms rely on human moderators to identify hate speech and take necessary action. However, with the increase in online hate speech, these platforms are turning toward automated hate speech detection and mitigation systems. This shift brings several challenges to the plate, and hence, is an important avenue to explore for the computation social science community.

We inquire into different perspectives and patterns of problematizing online hate speech within the social sciences from a systems-theoretical perspective. Our results identify five different research perspectives adopted by studies on the issue: (1) systematic perspectives on problems of operationalizing (online) hate speech; (2) intentionalist perspectives on actors and their motives; (3) consequentialist perspectives on victims of online hate speech; (4) perspectives on media affordances, infrastructures, and strategies of online hate speech; and finally, (5) normative perspectives on the consequences of online hate speech. Additionally, we want to propose a functionalist perspective on hate communication and, for this purpose, develop a systems-theoretical and media-sociological framework for analyzing online hate speech. A systems-theoretical perspective connects to a process-oriented paradigm of doing hate speech. Instead of asking what hate speech is, a systems-theoretical framework focuses on how different communicative contextures empirically produce different understandings of hate communication. We will make four research proposals: We will (1) conceptualize hate as hate communication, then proceed to (2) analyze different communicative contextures, (3) develop media archeology of negation and conflict communication, and finally (4) focus on the function of conflict and hate communication for the emergence of (counter-)publics.

The growth of online communities and social media has led to a growing need for methods, concepts, and tools for researching online cultures. Particular attention should be paid to polarizing online discussion cultures and dynamics that increase inequality in online environments. Social media has enormous potential to create good, but in order to unlock its full potential, we also need to examine the mechanisms keeping these spaces monotonous, homogenous, and even hostile toward some groups. With this need in mind, I have developed the concept and theory of othering online discourse (OOD). This chapter introduces and defines the concept of OOD and explains the key characteristics and different attributes of OOD in relation to other concepts that deal with disruptive and discriminatory behavior in online spaces. The attributes of OOD are demonstrated drawing on examples gathered from the Finnish Suomi24 (Finland24) forum.

Hate speech, or intentional derogatory expressions about people based on assigned group characteristics, has been studied primarily in online contexts. Less is known about the occurrence of this phenomenon in schools. As it has negative consequences for victims, perpetrators, and those who witness it, it is crucial to characterize the occurrence of offline (i.e., in the school) and online hate speech to describe similarities and differences between these two socialization contexts. The present study aimed to investigate the prevalence of hate speech witnessing, victimization, and perpetration, in a sample of 3,620 7–9th graders (51% self-identified as female) from 42 schools in Germany and Switzerland. We found that 67% of the students witnessed hate speech in their school, and 65% witnessed online hate speech at least once in the past 12 months. Approximately 21% of the students self-identified as offline perpetrators and 33% as offline victims, whereas these percentages were lower for online hate speech (13 and 20%, respectively). In both settings, skin color and origin were the most common group references for hate speech (50% offline and 63% online). Offline hate speech mainly came from classmates (88%), unknown sources (e.g., graffiti; 19%), or teachers (12%), whereas online hate speech mostly came from unknown persons (77%). The most frequent forms of offline hate speech were offensive jokes (94%) and the spread of lies and rumors about the members of a specific social group (84%). Significant differences by country, gender, and migration background were observed. Girls reported more offline victimization experiences, less perpetration, and a greater frequency of witnessing hate speech. This difference was larger in magnitude in the online setting. Students in Switzerland reported being exposed to hate speech more often than students in Germany. Students with a migration background reported higher hate speech victimization based on skin color and origin than students without a migration background. The high prevalence of hate speech highlights the need for school-based prevention programs. Our findings are discussed in terms of the practical implications.

This study examines the perceptions, behaviour, and digital experiences of African youth in relation to online misinformation and hate speech. Using a large-scale, cross-national survey with 10,005 valid responses, the research relies on both statistical clustering and deep learning-based autoencoder models to group youth together based on their trust in information, concern about misinformation, verification behaviours and platform usage. The dual-method analysis highlights three distinct behavioural and attitudinal clusters of youth, denoting different levels of digital skeptical engagement, exposure, and civic engagement. The findings highlight the heterogeneity within the youth population and emphasize that a one-size-fits-all approach to combating misinformation is insufficient. Notably, youth with high concern also demonstrated strong verification habits, while less engaged clusters exhibited low concern and limited digital resilience. These insights offer a foundation for designing cluster-specific interventions and media literacy strategies that are regionally and behaviourally responsive. This combination advances research through unsupervised deep learning on large social survey data, as well as demonstrating the utility of deep learning in revealing latent behaviours. The implications of this study's findings are timely for educators, policy makers and digital platforms more broadly, that want to foster informed and safe digital participation for African youth. As scalable, data-driven framework is a contribution towards an inclusive digital policy package for varied youth realities that exist in an African context.

The emergence of digital platforms has greatly increased the scope of free expression by enabling instantaneous cross-border opinion sharing. Article 19[1](a) of the Indian Constitution, which states that "everyone has right to express their own thoughts freely through various means such as printing, media, publishing, writings, signs etc., but they come with reasonable restrictions under Article 19[2] to maintain decency, social order and peace, security of state, friendly relations with international states, etc." In any case, the distinction between free expression and disparaging speech has become more hazy due to the proliferation of hate speech on digital platforms that incites violence, discrimination, or disrupts public order. Legal obscurity has resulted from selective enforcement and the lack of a precise legal definition of disparaging speech on the internet in India. Even with laws like the Information Technology Act of 2000, the Indian Penal Code (now known as the Bharatiya Nyaya Sanhita, 2023), and others, controlling hate speech online continues to be a difficult task. This study examines the tension between limiting online hate speech and defending free expression, highlighting the necessity of clear legal regulations, technological responsibility, and striking a balance between constitutional rights and social harmony on digital platforms.

Online hate speech (OHS) refers to discriminatory or offensive content shared via digital platforms that targets social groups. Synthesizing evidence on OHS directed at sexual and gender minorities (SGMs) is crucial, given the disproportionate online discrimination experienced by SGM people and its implications for well-being and social norms. This PRISMA-based systematic review synthesized quantitative studies in which the target of OHS content was SGM people, regardless of whether participants were SGM or non-SGM. We addressed four questions: (a) OHS definitions and operationalizations; (b) prevalence and risk factors of OHS; (c) psychological, behavioral, and social outcomes of exposure; and (d) behavioral responses to OHS exposure. Searches of 5 databases identified 13 studies. Definitions varied but generally captured identity-based targeting and hostile content in public or semi-public digital spaces. Prevalence varied by sampling frame: SGM-only studies reported high exposure (often > 85%), whereas general-population studies reported lower prevalence but higher exposure among SGM respondents. Risk factors were identity visibility/engagement, online behaviors, and lower digital media literacy; perpetration evidence was scarce. Exposure was associated with poorer SGM well-being (e.g., depression/anxiety, substance use, concealment, identity threat) and, experimentally, with lower perceived social cohesion and mixed effects on social attitudes. Witnesses generally condemned anti-SGM OHS; tolerance was higher among users with more negative pre-existing attitudes. Perceiving OHS as uncivil or harmful predicted stronger intervention intentions, while counter-speech effects were modest, reducing identity threat mainly under milder OHS. Findings highlight the need for harmonized measures, longitudinal/intersectional designs, and interventions pairing platform moderation with bystander-focused prevention efforts.

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

The rise in social media has led to an increase in abusive language online, necessitating effective solutions. This study introduces an automated model utilizing advanced frameworks for detecting and filtering abusive language and hate speech‐related text in social media posts. The proposed model is trained on a publicly available dataset and uses machine learning (ML) and deep learning (DL) models with features extracted from pre‐trained embedding vectors. The DL‐based model outperformed state‐of‐the‐art models. Human expertise is also used to validate misclassification. The model's performance was validated on a benchmark dataset, confirming its advantages over traditional frameworks. The proposed system can efficiently detect abusive, hate and offensive words with 89% accuracy and replace them with asterisks (*) in real‐time, fostering respectful conversations on social platforms. This research addresses the sociocultural impact of online hate speech and its regulation through technology. By bridging AI with social concerns, the study offers a robust framework to support healthier online discourse and reduce the prevalence of harmful content on digital platforms.

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

Since the official launch of online social networks in the 1990s, the number of users and offered services has risen progressively, affecting societies and daily life. In some cases, these online platforms have been a breeding ground for radical groups to share their point of view on migrants, leading to incidents of disinformation. On that note, the current research paper aims to examine the digital literacy rates in Bulgaria and Romania, the two EU Member States in Eastern Europe that recently entered the Schengen Area, and monitor the shift of public opinion towards migrants in recent years. Eventually, the paper demonstrates how the ability to track and report misleading information on migrant stories and integration policies in digital platforms can be a significant factor in reducing the spread of hate speech across different social groups. By utilizing a mixed-methods approach, namely investigating national reports on digital and media literacy, and tracking down the changes in public perception, this study sheds light on the initiatives implemented in those countries to combat hate speech and discrimination against migrants. Additionally, through the finding analysis, the paper concludes with key remarks on how policy recommendations can be formed based on decisions on regional and transnational levels. Ultimately, the study results can be the basis for future research on the correlation between education level and media interpretation.

In an era where digital interactions are increasingly prevalent, the challenge of effectively regulating online hate speech has emerged as a crucial societal concern. Balancing the regulation of such speech with the preservation of online freedom of expression is a delicate task, requiring broad consensus among internet users. This study delves into the various factors shaping public attitudes towards the regulation of online hate speech in South Korea. An online survey of 1,000 Internet users provided the data for a structural equation model. Our findings reveal that experiences of victimization by hate speech, online activity such as content uploading, assessment of social harm caused by online hate speech, and assessment on the effectiveness of regulatory measures all play significant roles in garnering support for regulation. Notably, online activity correlates strongly with increased encounters with hate speech. This, in turn, leads to a more profound understanding of its social harm and, consequently, a heightened inclination to support regulatory measures. These insights underscore the growing urgency to address online hate speech, especially as online activity continue to intensify. This study contributes to the discourse on online hate speech regulation by highlighting the complex interplay of personal experience, perceived harm, and efficacy of regulation in shaping public consensus.