On the Configuration of Crowdsourcing Projects

Crowdsourcing is an emerging paradigm, facilitated by the ease and scale of online connectivity, which harnesses the power of the crowds to solve problems and contribute knowledge. Crowdsourcing has been tried in practice and there are several commercial general-purpose crowdsourcing platforms on the web. Although the paradigm feasibility and impact have become evident, we still lack engineering methods and principles which aid the construction of quality crowdsourcing-based solutions. One of these aspects is the compatibility between the various configuration choices of the elements of a crowdsourcing project. In a previous work, the authors surveyed the literature and extracted a taxonomy of the various features which describes each of the four pillars of crowdsourcing: the crowd, the crowdsourcer, the crowdsourced task and the crowdsourcing platform. In this paper, the authors study the inter-relations between these features when configuring a crowdsourcing project. They start with an initial template and then confirm and enhance it by an expert study which involves 37 experts who applied crowdsourcing in practice and published research results. Their study helps crowdsourcers and crowdsourcing platform developers to better understand the several peculiarities that may arise by combining these features and thus assist them in the configuration of crowdsourcing projects with more awareness.

[1]  Andrea Chester,et al.  Online Teaching: Encouraging Collaboration through Anonymity , 2006, J. Comput. Mediat. Commun..

[2]  Kyo Chul Kang,et al.  Feature-Oriented Domain Analysis (FODA) Feasibility Study , 1990 .

[3]  Mark Wexler Reconfiguring the sociology of the crowd: exploring crowdsourcing , 2011 .

[4]  Duncan J. Watts,et al.  Financial incentives and the "performance of crowds" , 2009, SIGKDD Explor..

[5]  Daniel J. Veit,et al.  More than fun and money. Worker Motivation in Crowdsourcing - A Study on Mechanical Turk , 2011, AMCIS.

[6]  Henning Müller,et al.  Ground truth generation in medical imaging: a crowdsourcing-based iterative approach , 2012, CrowdMM '12.

[7]  Heiko Gewald,et al.  Does Money Matter? Motivational Factors for Participation in Paid- and Non-Profit-Crowdsourcing Communities , 2013, Wirtschaftsinformatik.

[8]  Jennifer Brown,et al.  Quitters Never Win: The (Adverse) Incentive Effects of Competing with Superstars , 2011, Journal of Political Economy.

[9]  V. Chanal,et al.  How to invent a new business model based on crowdsourcing: The crowdspirit ® case , 2008 .

[10]  Huiji Gao,et al.  Harnessing the Crowdsourcing Power of Social Media for Disaster Relief , 2011, IEEE Intelligent Systems.

[11]  Mahmood Hosseini,et al.  Towards Crowdsourcing for Requirements Engineering , 2014, REFSQ Workshops.

[12]  P. Whitla,et al.  Crowdsourcing and its application in marketing activities , 2009 .

[13]  Andrea Castelletti,et al.  Putting humans in the loop: Social computing for Water Resources Management , 2012, Environ. Model. Softw..

[14]  Daren C. Brabham MOVING THE CROWD AT THREADLESS , 2010 .

[15]  David Harvey,et al.  Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping , 2013, Astron. Comput..

[16]  Bei Yu,et al.  Crowdsourcing Participatory Evaluation of Medical Pictograms Using Amazon Mechanical Turk , 2013, Journal of medical Internet research.

[17]  Aderemi A. Atayero,et al.  Integrated Models for Information Communication Systems and Networks: Design and Development , 2013 .

[18]  Patrick Meier,et al.  Mobile Technology, Crowdsourcing and Peace Mapping: New Theory and Applications for Conflict Management , 2011 .

[19]  Frank van der Linden,et al.  Software product lines in action , 2007 .

[20]  Hye-Young Kim,et al.  Content Analysis of Online Co-Design Community Interactions: A Case Study of Crowd-Sourced Threadless , 2010 .

[21]  Jaejoon Lee,et al.  Concepts and Guidelines of Feature Modeling for Product Line Software Engineering , 2002, ICSR.

[22]  Jaejoon Lee,et al.  FORM: A feature-;oriented reuse method with domain-;specific reference architectures , 1998, Ann. Softw. Eng..

[23]  Aniket Kittur,et al.  Crowdsourcing user studies with Mechanical Turk , 2008, CHI.

[24]  Klaus Schmid,et al.  Software product lines in action - the best industrial practice in product line engineering , 2007 .

[25]  Nan Jiang,et al.  Crowdsourcing software evaluation , 2014, EASE '14.

[26]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[27]  Mahmood Hosseini,et al.  The four pillars of crowdsourcing: A reference model , 2014, 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS).