HCCYJul 5, 2015

Eventful: Crowdsourcing Local News Reporting

arXiv:1507.01300v19 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of efficient and low-cost local news reporting for communities, though it is incremental as it builds on existing crowdsourcing methods.

The authors tackled the problem of producing local news reports by developing Eventful, a system that uses remote and locative crowd workers to perform roles like field reporter, curator, and writer, resulting in reports completed in under an hour and costing under $150 USD.

We present Eventful, a system for producing news reports of local events using remote and locative crowd workers. The system recruits and guides novice crowd workers as they perform the roles of field reporter, curator, or writer. Field reporters attend the events in person, and use Eventful's mobile web app to get a personalized mission, submit content, and receive feedback. Missions include tasks such as taking a photo, and asking a question to an attendee. In parallel, remote curators approve, reject, and give real-time feedback on the content collected by field reporters. Finally, writers put together a report by mashing up and tweaking the content approved by the curators. We used Eventful to produce a news report for each of the six local events we decided to cover as we piloted the system. The process was typically completed under an hour and costing under $150 USD.

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