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This study analyzes cultural discourses around political deepfakes through mediaarchiving. Deepfakes use deep learning techniques to edit authentic media content and are currently impacting online political communication. To assess the field of discourse around political deepfakes, the study involved the creation of a database of digital media artifacts, including texts and audio-visual documents. The study relies on cultural analytics method to establish the patterns contained in media used to portray political deepfakes and their effects. Deepfakes continue to threaten democracies and erode trust in public institutions. Thus, studies that focus on the discourses around political deepfakes stand to increase and promote literacy about this important subject. / Media & Communication

Selective avoidance has been conceptualized and most often analyzed as a mirror image of selective exposure since the origins of political communication research (Lazarsfeld, Berelson, & Gaudet, 1948). However, recent studies have served to differentiate selective avoidance from selective exposure (Garrett, 2009a, 2009b; Garrett & Stroud, 2014; Song, 2017; Tsfati, 2016), and the current project explores the selective avoidance phenomenon at the individual, global, and macro-social levels. Secondary analyses were conducted on three reputable global-level data sets (i.e., World Values Survey [1981-2020, N = 174,450], European Values Studies [1981-2020, N = 114,983] and Digital News Report [2019, N = 75,749]) using a wide range of univariate and multivariate procedures. Results show that politically interested people are less likely to avoid news and people on the extreme ranges of political ideology tend to avoid news across the globe. Macro-level cultural values did not serve as a moderator, but other factors (e.g., Freedom House Index, Internet penetration rate, and Urbanization rate) moderated the relationship between political interest and extremity and selective news avoidance in a series of post-hoc tests. Individuals’ affective reaction to the news (i.e., being worn out by news) significantly predicts selective news avoidance. Stepping away from a consistency-based theoretical foundation, the current study has introduced affect as a new theoretical avenue that can direct future research on selective avoidance. / Media & Communication