Welcome to the workshop Weaving Relations of Trust in Crowd Work: Transparency and Reputation across Platforms co-located with WebSci16!
Despite the rapid growth of new platforms (e.g., CrowdFlower, Amazon Mechanical Turk, Upwork), crowdsourcing is still in its early stages. Many challenges remain to be addressed on the road to fair, high-quality platform-based work, as mentioned by Kittur et al.  and Demartini . Weaving relations of trust, analogously to the traditional workplace is key to improving crowd work environments and user experience (see also Motivation).
The goal of this workshop is to analyze different aspects of trust in online crowd work. We would like to discuss requirements, methods, techniques and studies that look into ways of boosting transparency and managing reputation of any of the participants in paid crowdsourcing (crowd workers, requesters and marketplaces) also looking at the trade-off with worker anonymity and privacy.
We will provide a dynamic framework for discussion among researchers, and other interested parties, including crowd workers, requesters and crowdsourcing platform managers. We expect contributions combining ideas from different disciplines, including Web Science, Computer-Supported Cooperative Work, Organizational and Social Psychology, Economics and Social Science broadly.
Highlights of the workshop:
- there will be a call-for-papers (see CFP)
- there will be a best paper award given by the crowd (i.e. CrowdFlower crowd workers)
- we will have a crowd statement marathon in which you could have a say! (see Crowd Statement Marathon)
Contact us via Twitter: @trustincw
Contact us via e-mail: firstname.lastname@example.org
Discuss the topic of trust in crowd work with us via Twitter: #trustincrowdwork
 Aniket Kittur, Jeffrey V. Nickerson, Michael Bernstein, Elizabeth Gerber, Aaron Shaw, John Zimmerman, Matt Lease, and John Horton. 2013. The future of crowd work. In Proceedings of the 2013 conference on Computer supported cooperative work (CSCW '13). ACM, New York, NY, USA, 1301-1318. DOI=http://dx.doi.org/10.1145/2441776.2441923
 Gianluca Demartini. Hybrid Human-Machine Information Systems: Challenges and Opportunities. In: Computer Networks, Special Issue on Crowdsourcing, Volume 90, page 5-13 (2015), Elsevier.