Abstract Political knowledge is fundamental to democratic politics. I develop a group-centered theory of political knowledge acquisition in the current media environment, which includes both high- and low-choice media, in this article. I argue that group identity prompts selective exposure to media content, which gives rise to specialized group-relevant political knowledge. This specialized knowledge is deeply relevant to the group and cannot be measured with indicators of general political knowledge. I show that selective exposure is the crucial mechanism facilitating specialized knowledge: Both selective exposure to Black-oriented content and use of high-choice media (the Internet) increase group-relevant knowledge among Black issue publics. This research speaks to scholarship examining the role of digital media in democratic politics and illustrates that the affordances of the Internet, and particularly selective exposure, are crucial to marginalized groups, who do not see their interests represented in mainstream media content, but who can access such information online.
{"title":"Black issue publics online: securing political knowledge through selective exposure","authors":"Mona S Kleinberg","doi":"10.1093/joc/jqad027","DOIUrl":"https://doi.org/10.1093/joc/jqad027","url":null,"abstract":"Abstract Political knowledge is fundamental to democratic politics. I develop a group-centered theory of political knowledge acquisition in the current media environment, which includes both high- and low-choice media, in this article. I argue that group identity prompts selective exposure to media content, which gives rise to specialized group-relevant political knowledge. This specialized knowledge is deeply relevant to the group and cannot be measured with indicators of general political knowledge. I show that selective exposure is the crucial mechanism facilitating specialized knowledge: Both selective exposure to Black-oriented content and use of high-choice media (the Internet) increase group-relevant knowledge among Black issue publics. This research speaks to scholarship examining the role of digital media in democratic politics and illustrates that the affordances of the Internet, and particularly selective exposure, are crucial to marginalized groups, who do not see their interests represented in mainstream media content, but who can access such information online.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136143599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article considers the Turing test as a problem of communication, particularly by asking how the language of artificial intelligence (AI) appears to human experience in comparison to the language of the Other. This question is approached through Levinas’ philosophy, by considering the possibility of AI as an absolute alterity, rather than reducing its alterity to the Same. This perspective diverges from traditional accounts of AI, which are more concerned with identifying structures of consciousness in the machine that are analogous to those evident in firsthand experience. This article asks how exactly AI appears to human consciousness, and whether this appearance precludes the appearance of AI as a thinking-being. In the final analysis, the author argues that AI diverges from Levinas’ understanding of alterity, which centers around the exteriority of the Other. The alterity of AI, in contrast, centers around anteriority, defined as the appearance of language's origin-in-itself.
{"title":"Phenomenology of the Turing test: a Levinasian perspective","authors":"Matthew S Lindia","doi":"10.1093/joc/jqad026","DOIUrl":"https://doi.org/10.1093/joc/jqad026","url":null,"abstract":"This article considers the Turing test as a problem of communication, particularly by asking how the language of artificial intelligence (AI) appears to human experience in comparison to the language of the Other. This question is approached through Levinas’ philosophy, by considering the possibility of AI as an absolute alterity, rather than reducing its alterity to the Same. This perspective diverges from traditional accounts of AI, which are more concerned with identifying structures of consciousness in the machine that are analogous to those evident in firsthand experience. This article asks how exactly AI appears to human consciousness, and whether this appearance precludes the appearance of AI as a thinking-being. In the final analysis, the author argues that AI diverges from Levinas’ understanding of alterity, which centers around the exteriority of the Other. The alterity of AI, in contrast, centers around anteriority, defined as the appearance of language's origin-in-itself.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"10 3","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ian Hawkins, Jessica Roden, Miriam Attal, Haleemah Aqel
Social media users often push back against harmful rhetoric with satirical and aggressive counterspeech. How do the interconnected race and gender identities of the person posting counterspeech and the person viewing it impact evaluations of the comment? Across two online experiments, we manipulate the race (Black or White) and gender (man or woman) of an individual whose tweet opposes ignorance about White privilege to examine if identity influences perceptions of incivility and intentions to flag the tweet for removal among Black and White men and women participants. Results demonstrate White men were most likely to find the tweet uncivil and report it, and this was especially the case when the tweet came from a Black woman, regardless of the tone. These studies highlight the importance of recognizing power and intersectionality in social media content moderation and creating policies that counteract the uniquely severe treatment of Black women by White men.
{"title":"Race and gender intertwined: why intersecting identities matter for perceptions of incivility and content moderation on social media","authors":"Ian Hawkins, Jessica Roden, Miriam Attal, Haleemah Aqel","doi":"10.1093/joc/jqad023","DOIUrl":"https://doi.org/10.1093/joc/jqad023","url":null,"abstract":"Social media users often push back against harmful rhetoric with satirical and aggressive counterspeech. How do the interconnected race and gender identities of the person posting counterspeech and the person viewing it impact evaluations of the comment? Across two online experiments, we manipulate the race (Black or White) and gender (man or woman) of an individual whose tweet opposes ignorance about White privilege to examine if identity influences perceptions of incivility and intentions to flag the tweet for removal among Black and White men and women participants. Results demonstrate White men were most likely to find the tweet uncivil and report it, and this was especially the case when the tweet came from a Black woman, regardless of the tone. These studies highlight the importance of recognizing power and intersectionality in social media content moderation and creating policies that counteract the uniquely severe treatment of Black women by White men.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"10 2","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid deployment of artificial intelligence (AI) technology has enabled AI agents to take on various roles as communicators, such as virtual assistants, robot journalists, and AI doctors. This study meta-analyzed 121 randomized experimental studies (N = 53,977) that compared the effects of AI and human agency on persuasion outcomes, including perceptions, attitudes, intentions, and behaviors. The results showed that AI agents were as persuasive as humans in terms of overall persuasion outcomes. With regard to different types of outcomes, AI was less effective than humans at shaping behavioral intentions, but did not differ significantly from humans in eliciting perceptions, attitudes, or actual behaviors. Additionally, heterogeneous patterns were observed for different roles of AI communicators, directions of communication, experimental settings, and demographic segments. The implications of these findings for human–machine communication and persuasion in the era of AI are discussed.
{"title":"Is artificial intelligence more persuasive than humans? A meta-analysis","authors":"Guanxiong Huang, Sai Wang","doi":"10.1093/joc/jqad024","DOIUrl":"https://doi.org/10.1093/joc/jqad024","url":null,"abstract":"The rapid deployment of artificial intelligence (AI) technology has enabled AI agents to take on various roles as communicators, such as virtual assistants, robot journalists, and AI doctors. This study meta-analyzed 121 randomized experimental studies (N = 53,977) that compared the effects of AI and human agency on persuasion outcomes, including perceptions, attitudes, intentions, and behaviors. The results showed that AI agents were as persuasive as humans in terms of overall persuasion outcomes. With regard to different types of outcomes, AI was less effective than humans at shaping behavioral intentions, but did not differ significantly from humans in eliciting perceptions, attitudes, or actual behaviors. Additionally, heterogeneous patterns were observed for different roles of AI communicators, directions of communication, experimental settings, and demographic segments. The implications of these findings for human–machine communication and persuasion in the era of AI are discussed.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"9 24","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the struggle to find sustainable business models, many local news sites have turned to engaged journalism, which draws from social exchange theory and aims to build relationships with audiences. The causal impact of these initiatives is unclear, but important given that local news sites are critical information sources and face dire economic situations. In this study, 20 news sites were randomly assigned to launch a six-month engaged journalism initiative where journalists reported on audience questions or to continue their current practices. Although not a panacea, over time traffic and subscription data and a two-wave survey of audience members across the sites (n = 3,998) show that the initiative resulted in more subscriptions and more positive audience evaluations. The results highlight the applicability of social exchange theory to questions of local news viability and illustrate that engaged journalism can improve relationships between newsrooms and the communities they serve.
{"title":"Curbing the decline of local news by building relationships with the audience","authors":"Natalie Jomini Stroud, Emily Van Duyn","doi":"10.1093/joc/jqad018","DOIUrl":"https://doi.org/10.1093/joc/jqad018","url":null,"abstract":"In the struggle to find sustainable business models, many local news sites have turned to engaged journalism, which draws from social exchange theory and aims to build relationships with audiences. The causal impact of these initiatives is unclear, but important given that local news sites are critical information sources and face dire economic situations. In this study, 20 news sites were randomly assigned to launch a six-month engaged journalism initiative where journalists reported on audience questions or to continue their current practices. Although not a panacea, over time traffic and subscription data and a two-wave survey of audience members across the sites (n = 3,998) show that the initiative resulted in more subscriptions and more positive audience evaluations. The results highlight the applicability of social exchange theory to questions of local news viability and illustrate that engaged journalism can improve relationships between newsrooms and the communities they serve.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"9 18","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emillie de Keulenaar, João C Magalhães, Bharath Ganesh
With their power to shape public discourse under unprecedented scrutiny, social media platforms have revamped their speech control practices in recent years by building complex systems of content moderation. The contours of this tectonic shift are relatively clear. Yet, little work has systematically documented, examined, and theorized this process. This article uses digital methods and web history to trace the evolution of objectionable content on Twitter content moderation policies and practices between 2006 and 2022. Its conclusions suggest that, more than abandoning an Americanized view of freedom of speech, Twitter has aimed at building a crisis-resistant speech architecture that can withstand external shocks, criticisms, and shifting speech norms. This kind of modulated moderation, as we term it, hinges on a form of normative plasticity, whose goal is not necessarily adjudicating content as more or less acceptable, but moderating it on the basis of evolving and ever contingent public conceptions of objectionability.
{"title":"Modulating moderation: a history of objectionability in Twitter moderation practices","authors":"Emillie de Keulenaar, João C Magalhães, Bharath Ganesh","doi":"10.1093/joc/jqad015","DOIUrl":"https://doi.org/10.1093/joc/jqad015","url":null,"abstract":"With their power to shape public discourse under unprecedented scrutiny, social media platforms have revamped their speech control practices in recent years by building complex systems of content moderation. The contours of this tectonic shift are relatively clear. Yet, little work has systematically documented, examined, and theorized this process. This article uses digital methods and web history to trace the evolution of objectionable content on Twitter content moderation policies and practices between 2006 and 2022. Its conclusions suggest that, more than abandoning an Americanized view of freedom of speech, Twitter has aimed at building a crisis-resistant speech architecture that can withstand external shocks, criticisms, and shifting speech norms. This kind of modulated moderation, as we term it, hinges on a form of normative plasticity, whose goal is not necessarily adjudicating content as more or less acceptable, but moderating it on the basis of evolving and ever contingent public conceptions of objectionability.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"11 2","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xuanjun Gong, Richard Huskey, Allison Eden, Ezgi Ulusoy
Mood management theory (MMT) hypothesizes that people select entertainment content to maintain affective homeostasis. However, this hypothesis lacks a formal quantification of each affective attributes’ separate impact on an individual’s media content selection, as well as an integrated cognitive mechanism explaining media selection. Here we present a computational decision-making model that mathematically formalizes this affective media decision-making process. We empirically tested this formalization with the drift-diffusion model using three decision-making experiments. Contrary to MMT, all three studies showed that people prefer negatively valenced and high-arousal media content and that prevailing mood does not shape media selection as predicted by MMT. We also discovered that people are less cautious when choices have larger valence differences. Our results support the proposed mathematical formalization of affective attributes’ influence on media selection, challenge core predictions drawn from MMT, and introduce a new mechanism (response caution) for media selection.
{"title":"Computationally modeling mood management theory: a drift-diffusion model of people’s preferential choice for valence and arousal in media","authors":"Xuanjun Gong, Richard Huskey, Allison Eden, Ezgi Ulusoy","doi":"10.1093/joc/jqad020","DOIUrl":"https://doi.org/10.1093/joc/jqad020","url":null,"abstract":"Mood management theory (MMT) hypothesizes that people select entertainment content to maintain affective homeostasis. However, this hypothesis lacks a formal quantification of each affective attributes’ separate impact on an individual’s media content selection, as well as an integrated cognitive mechanism explaining media selection. Here we present a computational decision-making model that mathematically formalizes this affective media decision-making process. We empirically tested this formalization with the drift-diffusion model using three decision-making experiments. Contrary to MMT, all three studies showed that people prefer negatively valenced and high-arousal media content and that prevailing mood does not shape media selection as predicted by MMT. We also discovered that people are less cautious when choices have larger valence differences. Our results support the proposed mathematical formalization of affective attributes’ influence on media selection, challenge core predictions drawn from MMT, and introduce a new mechanism (response caution) for media selection.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"10 1","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guided by the Social Identity Model of Collective Action, the current research utilizes a three-wave longitudinal study collected pre and post the 2020 U.S. Presidential election to examine the motivations underlying Latino Americans’ group-based social media engagement (N = 1,050). Results revealed that Time 1 group (Latino) identity increased Time 2 perceptions of social media as efficacious in improving group outcomes, which in turn increased Time 3 group-based social media engagement. Although T1 Latino identification was not significantly associated with T2 perceptions of personal or group-based injustice, the former (but not the latter) increased T3 group-based social media engagement. Our findings reflect that marginalized group members engage with social media in part because they believe it is efficacious in improving their disadvantageous group status. This may be an especially attractive strategy for those who face individual experiences of unjust treatment.
{"title":"Motivations underlying Latino Americans’ group-based social media engagement","authors":"Muniba Saleem, Dana Mastro, Meagan Docherty","doi":"10.1093/joc/jqad013","DOIUrl":"https://doi.org/10.1093/joc/jqad013","url":null,"abstract":"Guided by the Social Identity Model of Collective Action, the current research utilizes a three-wave longitudinal study collected pre and post the 2020 U.S. Presidential election to examine the motivations underlying Latino Americans’ group-based social media engagement (N = 1,050). Results revealed that Time 1 group (Latino) identity increased Time 2 perceptions of social media as efficacious in improving group outcomes, which in turn increased Time 3 group-based social media engagement. Although T1 Latino identification was not significantly associated with T2 perceptions of personal or group-based injustice, the former (but not the latter) increased T3 group-based social media engagement. Our findings reflect that marginalized group members engage with social media in part because they believe it is efficacious in improving their disadvantageous group status. This may be an especially attractive strategy for those who face individual experiences of unjust treatment.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"8 9","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social media metrics allow media outlets to get a granular, real-time understanding of audience preferences, and may therefore be used to decide what content to prioritize in the future. We test this mechanism in the context of Facebook, by using topic modeling and longitudinal data analysis on a large dataset comprising all posts published by major media outlets used by American citizens (N≈2.23M, 2015–2019). We find that while the overall effect of audience engagement on future news coverage is significant, there is substantial heterogeneity in how individual outlets respond to different kinds of topics. A handful of right-wing media outlets are more likely to respond to audience engagement metrics than other outlets, but with partisan politics topics and not with entertainment-oriented content. Our research sheds new light on how social media platforms have shaped journalistic practices and has implications for the future health of journalism in the United States.
{"title":"Metrics in action: how social media metrics shape news production on Facebook","authors":"Subhayan Mukerjee, Tian Yang, Yilang Peng","doi":"10.1093/joc/jqad012","DOIUrl":"https://doi.org/10.1093/joc/jqad012","url":null,"abstract":"Social media metrics allow media outlets to get a granular, real-time understanding of audience preferences, and may therefore be used to decide what content to prioritize in the future. We test this mechanism in the context of Facebook, by using topic modeling and longitudinal data analysis on a large dataset comprising all posts published by major media outlets used by American citizens (N≈2.23M, 2015–2019). We find that while the overall effect of audience engagement on future news coverage is significant, there is substantial heterogeneity in how individual outlets respond to different kinds of topics. A handful of right-wing media outlets are more likely to respond to audience engagement metrics than other outlets, but with partisan politics topics and not with entertainment-oriented content. Our research sheds new light on how social media platforms have shaped journalistic practices and has implications for the future health of journalism in the United States.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"116 8","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Numerous studies have shown that individuals’ belief sensitivity—their ability to discriminate between true and false political statements—varies according to psychological and demographic characteristics. We argue that sensitivity also varies with the political and social communication contexts in which they live. Both battleground state status of the state in which individuals live and the level of partisan segregation in a state are associated with Americans’ belief sensitivity. We leverage panel data collected from two samples of Americans, one collected in the first half of 2019 and the other during the 2020 U.S. presidential campaign season. Results indicate that the relationship between living in battleground states and belief sensitivity is contingent on political ideology: living in battleground states, versus in Democratic-leaning states, is associated with lower belief sensitivity among conservatives and higher belief sensitivity among liberals. Moreover, living in a less politically segregated state is associated with greater belief sensitivity. These relationships were only in evidence in the election year.
{"title":"Misperceptions in sociopolitical context: belief sensitivity’s relationship with battleground state status and partisan segregation","authors":"Qin Li, Robert M Bond, R Kelly Garrett","doi":"10.1093/joc/jqad017","DOIUrl":"https://doi.org/10.1093/joc/jqad017","url":null,"abstract":"Numerous studies have shown that individuals’ belief sensitivity—their ability to discriminate between true and false political statements—varies according to psychological and demographic characteristics. We argue that sensitivity also varies with the political and social communication contexts in which they live. Both battleground state status of the state in which individuals live and the level of partisan segregation in a state are associated with Americans’ belief sensitivity. We leverage panel data collected from two samples of Americans, one collected in the first half of 2019 and the other during the 2020 U.S. presidential campaign season. Results indicate that the relationship between living in battleground states and belief sensitivity is contingent on political ideology: living in battleground states, versus in Democratic-leaning states, is associated with lower belief sensitivity among conservatives and higher belief sensitivity among liberals. Moreover, living in a less politically segregated state is associated with greater belief sensitivity. These relationships were only in evidence in the election year.","PeriodicalId":48410,"journal":{"name":"Journal of Communication","volume":"116 3","pages":""},"PeriodicalIF":7.9,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50165168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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