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To what extent do journalists differ in their vulnerability to pressure from actors outside media organizations? This study complements research on such external interference by introducing the interference-vulnerability model. It typologizes three types of interference—professional, economic, and violent—that damage three basic motivations of journalists: professional status, economic status, and physical security. Further, it explains journalists’ experience of the three types of interference by their differing vulnerabilities, which stem from their value to external actors and the costs of noncompliance with interference. This argument builds on the theorized dynamic interaction between media professionals and external actors and applies the theory of routine activities and of rational choice. Multivariate regression of 567 journalists’ responses to a survey in Switzerland confirms the proposed model. Professional interference is aimed at informationally vulnerable journalists who publish on sensitive and investigative topics and have a wide reach. Economic interference is aimed at financially vulnerable journalists who cover consumer-oriented topics, have financial decision-making power, and work in economically competitive structures. Violent interference is directed against journalists who are vulnerable because of their identities: women and marginalized minorities. The model helps to explain external interference more comprehensively and to counter threats to journalistic autonomy. [ABSTRACT FROM AUTHOR]

Are people with lower social status more likely to post aggressive content online? And if yes, can this be explained by people's political views? Some previous attempts to approach these questions have been insufficiently comprehensive and methodologically sound. This study therefore expands the existing literature on online aggression with both a sociologically grounded, theoretical model of the interplay of social and political determinants and an innovative empirical data triangulation design. The study matches behavioral data from a social media platform with survey data providing extensive social and political information about users. Findings suggest that online aggression is more likely among users with an ascribed social status that is associated with power claims (male gender, older age, and national citizenship) and with a disadvantaged achieved social status (lower education, lower incomes, unemployment, and rural residence). Left–right leaning, populism, and trust in institutions can explain between 20 and 40 percent of these structural effects. The results help tailor measures that counter online aggression to specific risk groups. [ABSTRACT FROM AUTHOR]