Topics
Topics of interest include, but are not limited to:
Measuring trust
- Information needs of crowd workers, requesters and platforms
- Relevant data sources to foster trust among workers and requesters
- Extraction of explicit and implicit information from crowdsourcing data sources
- Subjective and behavioral assessments of trust (i.e., measures)
Building and reinforcing trust
- Relation between transparency, reputation and trust
- Trust in traditional workplace vs. the crowd “workplace”: similarities and differences
- Reputation in crowd work vs. reputation in other online systems (e.g., Airbnb)
- Monitoring reputation dynamics (e.g., preventing gaming of reputation mechanisms)
- New automatic and hybrid methods to build reputation out of available and reusable online data
- Identifying weaknesses and improving, e.g., qualifications
- Privacy concerns: What information may be public and which may be private? Who decides?
- Boosting direct communication to clarify and enhance reputation
- Incentives for opening crowdsourcing platform data
- Infrastructures for achieving transparency
- Socioeconomic consequences of crowd work reputation in digital labor platforms
Making use of reputational and other trust-related data
- Methods for multi-criteria work and people matchmaking
- Reputation-based crowd recruitment
- Cross-platform user authentication and data provenance verification methods
- Ethical aspects
- New interaction patterns (worker-worker, requester-requester, worker-requester, worker-platform owner and requester-platform owner interaction)
- Reputation management in new models for platform governance (e.g., cooperative platforms)
- Trust by design in new crowdsourcing platforms
We welcome discussions combining ideas from the following disciplines:
- Web Science
- Computer-Supported Cooperative Work
- Organizational and Social Psychology
- Economics
- Social Science