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Tutorial 5: Human Factors in Crowdsourcing

Presenters: Sihem Amer-Yahia (Univ. Grenoble Alps), Senjuti Basu Roy (New Jersey Inst. Tech.)
Date: Tue Sep 6 - Thu Sep 8, 2016
Time: 11.15 a.m. - 12.45 p.m.
Venue: Royal 2


Today, crowdsourcing is used to "taskify" any job ranging from simple receipt transcription to collaborative editing, fan-subbing, citizen science, and citizen journalism. The crowd is typically volatile, its arrival and departure asynchronous, and its levels of attention and accuracy diverse. Tasks vary in complexity and may necessitate the participation of workers with varying degrees of expertise. Sometimes, workers need to collaborate explicitly and build on each other's contributions to complete a single task. For example, in disaster reporting, CrowdMap allows geographically closed people with diverse and complementary skills, to work together to report details about the course of a typhoon or the aftermath of an earthquake.

This uber-ization of human labor requires the understanding of workers motivation in completing a task, their ability to work together in collaborative tasks, as well as, helping workers find relevant tasks. For over 40 years, organization studies have thoroughly examined human factors that affect workers in physical workplaces. More recently, computer scientists have developed algorithms that verify and lever- age those findings in a virtual marketplace, in this case, a crowdsourcing platform.

The goal of this tutorial is to review those two areas and discuss how their combination may improve workers' experience, task throughput and outcome quality for both microtasks and collaborative tasks. We will start with a coverage of motivation theory, team formation, and learning worker profiles. We will then address open research questions that result from this review.

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Sihem Amer-Yahia is DR1 CNRS at LIG in Grenoble where she leads the SLIDE team. Before joining CNRS, she was Principal Scientist at the Qatar Computing Research Institute, Senior Scientist at Yahoo! Research and AT&T Labs. Sihem has served on the SIGMOD Executive Board and on the PVLDB and the EDBT Endowments. She is the Editor-in-Chief of the VLDB Journal for Europe and Africa and is on the editorial boards of TODS and the Information System Journal. She is currently serving as area chair for SIGMOD 2016 and is co-chairing the PVLDB 2016 Workshops. Sihem received her Ph.D. in Computer Science from Paris-Orsay and INRIA in 1999.

Senjuti Basu Roy is an Assistant Professor at the Institute of Technology at the University of Washington Tacoma. Prior to joining UW in January 2012, she was a postdoctoral fellow at DIMACS at Rutgers University. Senjuti received her Ph.D. in Computer Science from UT Arlington in May 2011. Her research interests lie in the data and content management of web and structured data with a focus on exploration, analytics, and algorithms. Her research has been published in premier database and IR conferences and journals. Her past industrial experience includes working at Microsoft Research and IBM Research. She has co-chaired KDD Cup 2013, ExploreDB 2016, and serves as a guest editor of JMLR special issue on KDD Cup 2013.