7th IEEE International Workshop on Trusted Collaboration

Research Article

Reputation Management in Crowdsourcing Systems

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2012.250499,
        author={Mohammad Allahbakhsh and Aleksandar Ignjatovic and Boualem Benatallah and Seyed-Mehdi-Reza Beheshti and Elisa Bertino and Norman Foo},
        title={Reputation Management in Crowdsourcing Systems},
        proceedings={7th IEEE International Workshop on Trusted Collaboration},
        publisher={IEEE},
        proceedings_a={TRUSTCOL},
        year={2012},
        month={12},
        keywords={reputation degree of fairness crowdsourcing},
        doi={10.4108/icst.collaboratecom.2012.250499}
    }
    
  • Mohammad Allahbakhsh
    Aleksandar Ignjatovic
    Boualem Benatallah
    Seyed-Mehdi-Reza Beheshti
    Elisa Bertino
    Norman Foo
    Year: 2012
    Reputation Management in Crowdsourcing Systems
    TRUSTCOL
    ICST
    DOI: 10.4108/icst.collaboratecom.2012.250499
Mohammad Allahbakhsh1,*, Aleksandar Ignjatovic1, Boualem Benatallah1, Seyed-Mehdi-Reza Beheshti1, Elisa Bertino2, Norman Foo1
  • 1: UNSW
  • 2: Purdue University
*Contact email: mallahbakhsh@cse.unsw.edu.au

Abstract

Worker selection is a significant and challenging issue in crowdsourcing systems. Such selection is usually based on an assessment of the reputation of the individual workers participating in such systems. However, assessing the credibility and adequacy of such calculated reputation is a real challenge.

In this paper, we propose a reputation management model which leverages the values of the tasks completed, the credibility of the evaluators of the results of the tasks and time of evaluation of the results of these tasks in order to calculate more dependable quality metrics for workers and evaluators. The model has been implemented and experimentally validated.