Based on a qualitative survey among 203 US workers active on the microwork platform Amazon Mechanical Turk, we analyze potential biases embedded in the institutional setting provided by ondemand crowdworking platforms and their effect on perceived workplace fairness. We explore the triadic relationship between employers, workers, and platform providers, focusing on the power of platform providers to design settings and processes that affect workers' fairness perceptions. Our focus is on workers' awareness of the new institutional setting, frames applied to the mediating platform, and a differentiated analysis of distinct fairness dimensions.

Abstract

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.

No abstract

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.