CrowdSTAR: A Social Task Routing Framework for Online Communities

  • Besmira Nushi
  • Omar Alonso
  • Martin Hentschel
  • Vasileios Kandylas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)


The online communities available on the Web have shown to be significantly interactive and capable of collectively solving difficult tasks. Nevertheless, it is still a challenge to decide how a task should be dispatched through the network due to the high diversity of the communities and the dynamically changing expertise and social availability of their members. We introduce CrowdSTAR, a framework designed to route tasks across and within online crowds. CrowdSTAR indexes the topic-specific expertise and social features of the crowd contributors and then uses a routing algorithm, which suggests the best sources to ask based on the knowledge vs. availability trade-offs. We experimented with the proposed framework for question and answering scenarios by using two popular social networks as crowd candidates: Twitter and Quora.


Task routing Social search Question answering Crowdsourcing Expertise detection 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Besmira Nushi
    • 1
  • Omar Alonso
    • 2
  • Martin Hentschel
    • 3
  • Vasileios Kandylas
    • 2
  1. 1.Department of Computer ScienceETH ZurichZurichSwitzerland
  2. 2.Microsoft CorporationMountain ViewUSA
  3. 3.SnowFlake ComputingSan MateoUSA

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