Despite the increasing social media skepticism in an era of online misinformation, its sociopolitical consequences remain under-explored. This study is among a few that examine the effect of skepticism on online political engagement. With an online sample collected from the U.S., we find a negative impact of social media skepticism on online political participation, mediated by social media news use and expressive use. Furthermore, cognitive ability moderates this relationship, with the negative indirect effect being more pronounced among individuals with lower cognitive ability. This research highlights the potential democratic implications of social media skepticism and enriches the knowledge of its underlying psychological mechanisms. Moreover, it offers a nuanced understanding of the contingent effect of cognitive ability, suggesting its crucial role in mitigating social media skepticism’s adverse effects. This research provides valuable insights for navigating the evolving media landscape.

Artificial intelligence (AI) driven matchmaking algorithms are at the core of modern-day dating. Millions of users rely on these algorithms used by online dating platforms for successful matchmaking. However, a scholarly understanding of user perceptions of AI-driven matchmaking algorithms is limited. We explore the factors affecting users’ perceived effectiveness of matchmaking algorithms and analyze how users’ perception of AI’s fairness, social presence, and the threat posed by AI are associated with their perceived effectiveness of matchmaking algorithms. We also investigate if their previous relationship initiation experience through online dating platforms further moderates the studied relationships. An analysis of survey data from Singapore suggests that those who perceive AI to be fair and have higher levels of social presence are more likely to showcase a higher degree of perceived effectiveness of matchmaking algorithms. Moreover, those who have previously been successful in online dating relationship initiation are also more likely to believe in the perceived effectiveness of these algorithms. Further, previous experience of relationship initiation conditionally impacts the relationship between users’ general AI perceptions and perceived effectiveness. We also find that males and younger respondents are more likely to believe in the efficacy of matchmaking algorithms. Practical implications are offered.

As the 2020 United State Presidential election presented tense partisan conflicts, we sought to explore whether and how such a social and ideological fissure can lead to large-scale politically motivated avoidance behaviours. Building on prior literature, we examine how social media behaviours (i.e. expressive social media news use and political discussion with weak ties) and social psychological attitudes (i.e. surveillance anxiety) are associated with selective avoidance on social media. Further, we explore cognitive ability's direct and indirect roles in influencing avoidance behaviours. We used online panel survey data collected during the 2020 election to test our assumptions. The findings suggest that those with high levels of expressive social media news use, political discussions with weak ties, and surveillance anxiety engage in more frequent selective avoidance. On the contrary, those with high cognitive ability are less likely to engage in selective avoidance. Furthermore, moderation effects suggest that low cognitive users with greater surveillance anxiety and frequent discussions with weak ties are most accustomed to selective avoidance. Finally, we discuss the theoretical and policy implications of these findings.

This study investigates how politicians and citizens cooperate to create an e-democracy based on information dissemination and political awareness in an ICT environment, especially during elections. This research is conducted in the Indian context, where new ICT channels, such as Facebook and Twitter, were extensively used for campaigning and citizen engagement prior to elections. We downloaded 98,396 tweets posted by the official Twitter accounts of the top ten political parties during a two month period prior to election and conducted a three-level analysis to identify the overall trend in usage, the interactive characteristics of tweets and the functions driving the Twitter usage of political parties. Our findings show that the more successful parties used Twitter to push timely updates on online and offline campaign activities, to their followers. The exemplary use of Twitter for campaigns was by the Bharatiya Janta Party (BJP) Twitter account for interacting with the public, and by the Aam Aadmi Party (AAP) account for self-promotion and highlighting its party manifesto. Further, we identify the new paradigms created by political parties to engage and inform voters, driven on modern ICT. Our study is the first in analyzing Twitter usage by Indian political parties, and its findings corroborate seminal research in other developing countries.