Abstract Algorithms play a critical role in steering online attention on social media. Many have alleged that algorithms can perpetuate bias. This study audited shadowbanning, where a user or their content is temporarily hidden on Twitter. We repeatedly tested whether a stratified random sample of American Twitter accounts (n ≈ 25,000) had been subject to various forms of shadowbans. We then identified the type of user and tweet characteristics that predict a shadowban. In general, shadowbans are rare. We found that accounts with bot-like behavior were more likely to face shadowbans, while verified accounts were less likely to be shadowbanned. The replies by Twitter accounts that posted offensive tweets and tweets about politics (from both the left and the right) were more likely to be downtiered. The findings have implications for algorithmic accountability and the design of future audit studies of social media platforms.

Abstract Drawing from established theoretical traditions in cognitive consistency, motivated reasoning, heuristic–systematic processing, and the anger-activism model, we extend existing work linking anger with misperceptions by specifying three distinct ways anger might contribute to the formation of misperceptions: Increasing reliance on partisan heuristics, influencing political information-seeking behavior, and moderating the influence of partisan media exposure. Analyzing data from an original survey administered nationally via Qualtrics Panels during the first impeachment trial of President Donald Trump in January 2020, results indicate that high-anger partisans were more likely to express belief in claims supportive of their party and critical of the other party, regardless of the veracity of those claims. Further, anger was also linked with greater use of pro-attitudinal information sources and avoidance of counterattitudinal sources, with these differences in partisan media consumption subsequently influencing factual beliefs. However, we found no evidence that anger moderated the relationship between partisan media exposure and factual beliefs. We explore the implications of these findings in a political era defined increasingly by the experience of anger.

Journal Article Mental health among higher education faculty, administrators, and graduate students, Teresa Heinz Housel Get access Mental health among higher education faculty, administrators, and graduate students Teresa Heinz Housel, Lexington Books, New York, 2021, $120, 332 pp. Lindsey S Aloia Lindsey S Aloia Department of Communication, University of Arkansas, USA aloia@uark.edu Search for other works by this author on: Oxford Academic Google Scholar Journal of Communication, jqac029, https://doi.org/10.1093/joc/jqac029 Published: 15 November 2022 Article history Received: 02 August 2022 Revision received: 02 August 2022 Accepted: 07 August 2022 Published: 15 November 2022

Abstract The rapid proliferation and maturation of social media platforms have led to numerous challenges in understanding the correlates of social media use among users. To advance this research, the present article proposes a new way to think about social media with the Personal Social Media Ecosystem Framework (PSMEF). This perspective defines social media as a user-centric digital environment made up of a central set of individual, yet interrelated digital spaces (e.g., in-app pages) that are themselves embedded within a broader ecology (e.g., operating system, the Internet, offline contexts). By leveraging the PSMEF and data from focus groups involving adolescent participants (N = 59), we identify a core subset of salient environmental contexts within participants’ PSMEs that can generalize across platforms, which are differentially associated with popular social media platforms. The theoretical and practical implications of this work are discussed.

Abstract A heuristic model aims to organize and synthesize the substantial body of work examining the social influences that shape media selection, experiences, and effects. The Social Influences and Media Use (SIMU) model describes three broad social forces (users’ internal social needs, their social environment, and the social affordances of media) and their recursive association with media use. This article (a) brings together diverse subdisciplines interested in the social factors and functions of media use, (b) discusses the micro–macro nature of social phenomena and its potential role in future inquires, and (c) illustrates how the model might foster new developments by applying it in a specific area of study. The model may help us identify cohesive patterns (and points of divergence or uniqueness) among existing findings as well as inform future work examining these relationships across a variety of social contexts and media channels.

Abstract This study advances communication-centered resilience theory by examining adaptive capacity of nonprofit networks impacted by Hurricane Harvey in 2017. Data show how formal structures set up conditions for adaptive/informal organizing. This highlights a quandary for disaster planning: improvising emerges from organizations having plans in place. Iterative processes between formal and informal structures expanded capacity, building a foundation for work processes to scaffold from individual to organizational to interorganizational networks. Yet some employees were personally vulnerable, revealing a multilevel dilemma: organizations were resilient even if employees were not. This study also theorizes time as an endogenous mechanism. As workers perceived less urgency, process experts broadened communication across levels, integrating more complex work processes. Resilience differed between organizations that lacked process experts, revealing their critical role across levels. Findings point to a policy-making dilemma: successful resilience processes undermine pressure on policy-makers to mitigate threats that necessitate improving resilience processes to begin with.

Abstract Prior literature on political filter bubbles suggests an overall positive association between social media use and political networks diversification. Sometimes, this might not be the case. This study argues that the News Finds Me perception (NFM) or the belief that “one” can be well-informed about public affairs without actively seeking information as news will find “me” through “my” networks, tend to nurture a positive attitude toward algorithmic news gatekeeping. Likewise, NFM’s news over-reliance on one’s social network support the development of homogeneous information and discussion political networks in social media (political homophily). Results based on a variety of ordinary least squares regression models (cross-sectional, lagged, and autoregressive) from a U.S. representative panel survey, as we all as autoregressive structural equation model tests, indicate that this is indeed the case. This study serves to specifically clarify when and how social media and the NFM facilitate politically homogeneous filter bubbles.

Abstract Three criteria for political learning are opportunity, ability, and motivation. Models of passive learning call into question whether motivation is a necessary condition for learning about politics. Passive learning contends that incidental, or unintended, exposure to political content can produce learning among those unmotivated to view the content. To date, researchers have not found a way to conclusively test the idea of passive learning. By designing an experiment that gives individuals a choice in media content, we propose one strategy for testing passive learning among the unmotivated. Across four studies, the results illustrate limitations on the circumstances under which passive learning occurs and suggest that learning results from situations where incidental exposure sparks motivation.

Purpose: There has been lots of positive and negative criticisms on the influences and effects of animated images on kids in Nigeria without considering the communicative potentials of such medium from our cultural perspectives. Again, many Nigerians may not have the knowledge that there are quality Nigerian local content animation. Methodology: This paper looks at the perception of computer generated imagery (CGI) in Nigerian animated films. It examines the nature of the application of CGI in popular Nigerian Animated films by analyzing the techniques used and meanings produced from The images constructed to communicate the ideas of the narratives. This paper is anchored on the framework of cognitive semiotic theory and adopts the qualitative research design to investigate the communication of meanings by use of CGI in Malika (2020), the basis for using cognitive semiotic theory in this paper is that CGI are simulated believable images that denote meanings to communicate encoded cultural ideologies to kids within and outside Nigeria. It is hoped that this study would make better appreciation of Nigerian Animated films and encourage Animators to make more. Findings: The findings in this study, is that, the use of CGI in object and character representation in Nigerian Animated films as regards reality simulates the simulacra nature of a typical African worldview and bring to life a historical antecedent. It submits that CGI boosts the visual and aural representation of the Nollywood film narratives which allow the viewer to recognize the already established meanings of the codes used in film text. Unique Contribution to Theory, Practice and Policy: It also recommends that Animation should be used for promotion and preservation of fast fading Igbo cultures