{"id":168657,"date":"2015-08-01T00:00:00","date_gmt":"2015-08-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/crowdsourcing-in-the-field-a-case-study-using-local-crowds-for-event-reporting\/"},"modified":"2020-04-03T18:01:37","modified_gmt":"2020-04-04T01:01:37","slug":"crowdsourcing-in-the-field-a-case-study-using-local-crowds-for-event-reporting","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/crowdsourcing-in-the-field-a-case-study-using-local-crowds-for-event-reporting\/","title":{"rendered":"Crowdsourcing in the Field: A Case Study Using Local Crowds for Event Reporting"},"content":{"rendered":"<p>While crowd work typically involves tasks that performed at any time and anywhere, some tasks inherently require the physical presence of workers at a specific time and location. This paper presents a case study of a hybrid crowdsourcing process that involves the collaborative production of event reports using a combination of local and remote workers. The process extends human computation into the physical world by using local workers to collect information in person at events and remote workers to curate the collected information and generate event reports. We deployed the process at 11 events, employing 84 workers, and identified the challenges local workers face as constraints in mobility, time available to perform tasks, unpredictability of events, and interaction with others. We discuss issues related to collaboration with remote workers and bias in field reporting, and conduct a qualitative analysis to make design recommendations for extending human computation into the physical environment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>While crowd work typically involves tasks that performed at any time and anywhere, some tasks inherently require the physical presence of workers at a specific time and location. This paper presents a case study of a hybrid crowdsourcing process that involves the collaborative production of event reports using a combination of local and remote workers. 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