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The use of colocation and flow networks in mobile crowdsourcing

Published: 07 September 2015 Publication History

Abstract

Requesting relevant tasks to mobile crowds is extremely difficult without considering their movements. We propose an approach to geo-cast crowdsourcing tasks based on networks of human flows, and show that our approach can achieve higher geographical relevance than simple proximity-based approaches.

References

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Djellel Eddine Difallah, Gianluca Demartini, and Philippe Cudré-Mauroux. 2013. Pick-a-crowd: tell me what you like, and i'll tell you what to do. In Proceedings of the 22nd international conference on World Wide Web (WWW '13), 367--374.
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Simo Hosio, Jorge Goncalves, Vili Lehdonvirta, Denzil Ferreira, and Vassilis Kostakos. 2014. Situated crowdsourcing using a market model. In Proceeding of the 27th annual ACM Symposium on User Interface Software and Technology (UIST '14), 55--64. http://dx.doi.org/10.1145/2642918.2647362
[3]
Shin'ichi Konomi. 2011. Colocation Networks: exploring the use of social and geographical patterns in context-aware services. In Adjunct Proceedings of the 13th international Conference on Ubiquitous Computing (UbiComp '11), 565--566. http://dx.doi.org/10.1145/2030112.2030215
[4]
PFLOW. 2015. Retrieved July 7, 2015 from http://pflow.csis.u-tokyo.ac.jp/.
[5]
Sasank Reddy, Deborah Estrin, and Mani Srivastava. 2010. Recruitment framework for participatory sensing data collections. In Proceedings of the 8th International Conference on Pervasive Computing (Pervasive '10), 138--155. http://dx.doi.org/10.1007/978-3-642-12654-3_9
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Martin Rosvall and Carl T. Bergstrom. 2008. Maps of information flow reveal community structure in complex networks. PNAS, 105, 4: 1118--1123.
[7]
Man-Ching Yuen, Irwin King, and Kwong-Sak Leung. 2015. TaskRec: a task recommendation framework in crowdsourcing systems. Neural Processing Letters, 41, 2: 223--238.

Cited By

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  • (2024)“I Prefer Regular Visitors to Answer My Questions”: Users’ Desired Experiential Background of Contributors for Location-based Crowdsourcing PlatformProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642520(1-18)Online publication date: 11-May-2024
  • (2017)An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-word settingsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.11.001102:C(81-102)Online publication date: 1-Jun-2017

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  1. The use of colocation and flow networks in mobile crowdsourcing

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    cover image ACM Conferences
    UbiComp/ISWC'15 Adjunct: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers
    September 2015
    1626 pages
    ISBN:9781450335751
    DOI:10.1145/2800835
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    New York, NY, United States

    Publication History

    Published: 07 September 2015

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    Author Tags

    1. community detection
    2. complex networks
    3. mobile crowdsourcing
    4. mobility
    5. situated crowdsourcing

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    UbiComp '15
    Sponsor:
    • Yahoo! Japan
    • SIGMOBILE
    • FX Palo Alto Laboratory, Inc.
    • ACM
    • Rakuten Institute of Technology
    • Microsoft
    • Bell Labs
    • SIGCHI
    • Panasonic
    • Telefónica
    • ISTC-PC

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    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    Cited By

    View all
    • (2024)“I Prefer Regular Visitors to Answer My Questions”: Users’ Desired Experiential Background of Contributors for Location-based Crowdsourcing PlatformProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642520(1-18)Online publication date: 11-May-2024
    • (2017)An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-word settingsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.11.001102:C(81-102)Online publication date: 1-Jun-2017

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