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                  <text>VOL 27 ISSUE 4 2022</text>
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                <text>Youths as targets: factors of online hate speech victimization among adolescents and young adults</text>
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                <text>online hate speech, routine activity theory, victimization, adolescents and young adults, digital media literacy</text>
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                <text>A significant number of adolescents and young adults are targeted by online hate speech. The effect of such hateful utterances can involve severe psychological harm, especially for youths who have to master developmental tasks. Therefore, drawing on criminology’s routine activity theory, this study investigates the factors that help explain why youths become victimized through online hate speech. We conducted a national quota-based quantitative online survey that was representative of adolescent and young adult online users (N ¼ 1,180). In the results, we identified six latent profiles of young targets with overall high or low online hate speech victimization, victimization due to gender, migration background, religion, or political engagement on behalf of the queer community. While relative subjective deprivation, political participation, and lower digital media literacy positively predicted overall victimization through online hate speech, being targeted was more likely for members of the aforementioned social groups and those showing political engagement.</text>
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                <text>Magdalena Obermaier, Desire´ e Schmuck</text>
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                <text>https://doi.org/10.1093/jcmc/zmac012</text>
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                <text>Oxford University Press</text>
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                <text>2 June 2022</text>
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                <text>Sri Wahyuni</text>
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                <text>English</text>
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                <text>Journal of Computer-Mediated Communication, 2022</text>
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                  <text>VOL 27 ISSUE 4 2022</text>
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                <text>A typology of social media rituals</text>
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                <text>genres, rituals, social media rituals, user-generated content, values</text>
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                <text>Given its massive volume and rapid development of new trends, the universe of user-generated content may seem utterly chaotic. Yet the flow of content is underlined by deep-rooted patterns of communication. In this article, we present the first systematic attempt to identify these pat�terns using the concept of social media rituals. Understood as typified communicative practices that formalize and express shared values, rituals&#13;
offer a productive path to categorize popular genres of content and trace the values they convey. Integrating theoretical literature on rituals with&#13;
empirical studies of social media genres, we develop a typology of 16 rituals that express diverse values, ranging from respect and responsibility to materialism and pleasure. Furthermore, we show that rituals embed different notions of good communication, as reflected in the values of&#13;
authenticity, persuasion, affiliation, and demonstration. Finally, we discuss how our framework can facilitate comparative investigations of usergenerated content and platform values.</text>
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                <text>Tommaso Trillo`, Blake Hallinan, Limor Shifman</text>
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                <text>https://doi.org/10.1093/jcmc/zmac011</text>
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                <text>Sri Wahyuni</text>
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                <text>English</text>
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                <text>Journal of Computer-Mediated Communication, 2022</text>
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                  <text>VOL 27 ISSUE 4 2022</text>
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                <text>When AI moderates online content: effects of human collaboration and interactive transparency on user trust</text>
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                <text>human-AI collaboration, content classification, source cues, interactivity, HAII-TIME model</text>
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                <text>Given the scale of user-generated content online, the use of artificial intelligence (AI) to flag problematic posts is inevitable, but users do not trust such automated moderation of content. We explore if (a) involving human moderators in the curation process and (b) affording “interactive transparency,” wherein users participate in curation, can promote appropriate reliance on AI. We test this through a 3 (Source: AI, Human, Both) � 3&#13;
(Transparency: No Transparency, Transparency-Only, Interactive Transparency) � 2 (Classification Decision: Flagged, Not Flagged) between�subjects online experiment (N ¼ 676) involving classification of hate speech and suicidal ideation. We discovered that users trust AI for the mod�eration of content just as much as humans, but it depends on the heuristic that is triggered when they are told AI is the source of moderation. We also found that allowing users to provide feedback to the algorithm enhances trust by increasing user agency </text>
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                <text>Maria D. Molina , S. Shyam Sundar</text>
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                <text>https://doi.org/10.1093/jcmc/zmac010</text>
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                <text>16 May 2022</text>
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                <text>Sri Wahyuni</text>
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                <text>Journal of Computer-Mediated Communication, 2022</text>
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                  <text>VOL 27 ISSUE 4 2022</text>
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            <description>A name given to the resource</description>
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                <text>The Fake One is the Real One: Finstas, Authenticity, and Context Collapse in Teen Friend Groups</text>
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                <text>Research has shown that as individuals—particularly teenagers—navigate social media, they value authenticity, typically understood as congruence between their online and offline identities. Portraying oneself in an authentic manner, however, is complicated by the phenomenon of con�text collapse, where multiple audiences (e.g., friends, teachers, parents) become homogenized and boundaries become blurred. Drawing on focus group data with 20 teenagers aged 13–17, we examined how teens use Finstas (“fake Instagram” accounts) to navigate tensions between context collapse and authenticity. Our participants see themselves as quite skilled at creating idealized identities on their Rinstas (“real&#13;
Instagram” accounts) but turn to Finstas because they find such performances unsatisfying, using these secondary accounts for active resis�tance to norms of mainstream Instagram, often through negative emotional expression and self-description. Our study adds to the literature on teen social media use by illuminating strategies teens use to navigate context collapse as they seek authenticity.</text>
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                <text>Christopher R. Darr,  Erin F. Doss</text>
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                <text>https://doi.org/10.1093/jcmc/zmac009</text>
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                <text>Oxford University Press</text>
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                <text>4 May 2022</text>
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                <text>Sri Wahyuni</text>
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                <text>The detection of political deepfakes</text>
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                <text>Deepfake technology, allowing manipulations of audiovisual content by means of artificial intelligence, is on the rise. This has sparked concerns about a weaponization of manipulated videos for malicious ends. A theory on deepfake detection is presented and three preregistered studies examined the detection of deepfakes in the political realm (featuring UK’s Prime Minister Boris Johnson, Studies 1–3, or former U.S. President Barack Obama, Study 2). Based on two system models of information processing as well as recent theory and research on fake news, individual&#13;
differences in analytic thinking and political interest were examined as predictors of correctly detecting deepfakes. Analytic thinking (Studies 1 and 2) and political interest (Study 1) were positively associated with identifying deepfakes and negatively associated with the perceived accu�racy of a fake news piece about a leaked video (whether or not the deepfake video itself was presented, Study 3). Implications for research and practice are discussed. </text>
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                <text>Markus Appel, Fabian Prietzel</text>
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                <text>Sri Wahyuni</text>
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                <text>Journal of Computer-Mediated Communication, 2022</text>
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