This paper presents a systematic literature review of the current state–of–research on online participation. The review draws on four databases and is guided by the application of six topical search terms. The analysis strives to differentiate distinct forms of online participation and to identify salient discourses within each research field. We find that research on online participation is highly segregated into specific sub–discourses that reflect disciplinary boundaries. Research on online political participation and civic engagement is identified as the most prominent and extensive research field. Yet research on other forms of participation, such as cultural, business, education and health participation, provides distinct perspectives and valuable insights. We outline both field–specific and common findings and derive propositions for future research.
Social media are becoming increasingly popular in scientific communication. A range of platforms, such as academic social networking sites (SNS), are geared specifically towards the academic community. Proponents of the altmetrics approach have pointed out that new media allow for new avenues of scientific impact assessment. Traditional impact measures based on bibliographic analysis have long been criticized for overlooking the relational dynamics of scientific impact. We therefore propose an application of social network analysis to researchers' interactions on an academic social networking site to generate potential new metrics of scientific impact. Based on a case study conducted among a sample of Swiss management scholars, we analyze how centrality measures derived from the participants' interactions on the academic SNS ResearchGate relate to traditional, offline impact indicators. We find that platform engagement, seniority, and publication impact contribute to members' indegree and eigenvector centrality on the platform, but less so to closeness or betweenness centrality. We conclude that a relational approach based on social network analyses of academic SNS, while subject to platform-specific dynamics, may add richness and differentiation to scientific impact assessment.
How does the public perceive facial recognition technology and how much do they accept facial recognition technology in different political contexts? Based on online surveys resembling the Internet-connected population in China, Germany, the United Kingdom, and the United States, our study finds that facial recognition technology enjoys generally highest acceptance among respondents in China, while acceptance is lowest in Germany, and the United Kingdom and the United States are in between. A closer examination through the lens of an integrated technology acceptance model reveals interesting variations in the selected four countries based, among other factors, on socio-demographic factors as well as perceived consequences, usefulness, and reliability of facial recognition technology. While previous research has pointed out that facial recognition technology is an instrument for state surveillance and control, this study shows that surveillance and control are not foremost on the minds of citizens in China, Germany, the United Kingdom, and the United States, but rather notions of convenience and improved security.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.