Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

2-2017

Abstract

This paper establishes the power of dynamic collaborative task completion among workers for urban mobile crowdsourcing. Collaboration is defined via the notion of peer referrals, whereby a worker who has accepted a location-specific task, but is unlikely to visit that location, offloads the task to a willing friend. Such a collaborative framework might be particularly useful for task bundles, especially for bundles that have higher geographic dispersion. The challenge, however, comes from the high similarity observed in the spatiotemporal pattern of task completion among friends. Using extensive real-world crowd-sourcing studies conducted over 7 weeks and 1000+ workers on a campus-based crowd-sourcing platform, we quantify the effect of such "task completion homophily", and show that incorporating such peer-preferences can improve worker-specific models of task preferences by over 30%. We then show that such collaborative offloading works in spite of such spatio-temporal similarity, primarily because workers refer tasks to their close friends, who in turn perform such peer-requested tasks (with over 95% completion rate) even if they experience detours that are significantly larger (often more than twice) than what they normally tolerate for platform-recommended tasks.

Keywords

Collaboration, Crowd-sourcing, Homophily, Social-ties

Discipline

Databases and Information Systems | Software Engineering

Publication

Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, Oregon, USA, 2017 February 25 - March 1

First Page

902

Last Page

915

ISBN

9781450343350

Identifier

10.1145/2998181.2998311

Publisher

Association for Computing Machinery

City or Country

Portland

Additional URL

http://doi.org./10.1145/2998181.2998311

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