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Fueled by ever-growing amounts of (digital) data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, (public) health, and judicial contexts. Data from a scenario-based survey experiment with a national sample (N = 958) show that people are by and large concerned about risks and have mixed opinions about fairness and usefulness of automated decision-making at a societal level, with general attitudes influenced by individual characteristics. Interestingly, decisions taken automatically by AI were often evaluated on par or even better than human experts for specific decisions. Theoretical and societal implications about these findings are discussed.

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Personally managing and protecting online privacy has become an essential part of everyday life. This research draws on the protection motivation theory (PMT) to investigate privacy protective behavior online. A two-wave panel study (N = 928) shows that (1) people rarely to occasionally protect their online privacy and (2) people most often delete cookies and browser history or decline cookies to protect their online privacy. In addition, (3) the perceived threat is high: People perceive the collection, usage, and sharing of personal information as a severe problem to which they are susceptible. The coping appraisal is mixed: Although people do have confidence in some protective measures, they have little confidence in their own efficacy to protect their online privacy. Moreover, privacy protective behavior is affected by perceived severity and response efficacy. These findings emphasize the relevance of the PMT in the context of privacy threats, and have important implications for regulators.

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Political parties and politicians increasingly use the possibilities of the Internet to communicate interactively with citizens and vice versa. The Internet also offers opportunities for individual politicians to profile themselves. These developments are often said to bring politics closer to citizens, increasing their political engagement in politics. Empirical evidence for such claims is, however, scarce. In a scenario experiment and a laboratory experiment using real-world websites, the authors examine whether more personalized online communication (a focus on individual politicians) and the use of interactive features increase political involvement among citizens. The results from both studies demonstrate that both highly interactive and personalized online communication do increase citizens’ political involvement. Moreover, it was also found that political personalization positively moderates the effect of interactivity on political involvement, meaning that the effects of interactivity are even stronger in a personalized setting.

The privacy calculus suggests that online self-disclosure is based on a cost-benefit trade-off. However, although companies progressively collect information to offer tailored services, the effect of both personalization and context-dependency on self-disclosure has remained understudied. Building on the privacy calculus, we hypothesized that benefits, privacy costs, and trust would predict online self-disclosure. Moreover, we analyzed the impact of personalization, investigating whether effects would differ for health, news, and commercial websites. Results from an online experiment using a representative Dutch sample (N = 1,131) supported the privacy calculus,

This review article provides a critical discussion of empirical studies that deal with the use of online news sources in journalism. We evaluate how online sources have changed the journalist–source relationship regarding selection of sources as well as verification strategies. We also discuss how the use of online sources changes audience perceptions of news. The available research indicates that journalists have accepted online news sourcing techniques into their daily news production process, but that they hesitate to use information retrieved from social media as direct and quoted sources in news reporting. Studies show that there are differences in the use of online sources between media sectors, type of reporting, and country context. The literature also suggests that verification of online sources requires a new set of skills that journalists still struggle with. We propose a research agenda for future studies.