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Journalists as Crowdsourcerers: Responding to Crisis by Reporting with a Crowd

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Abstract

Widespread adoption of new information communication technologies (ICTs) is disrupting traditional models of news production and distribution. In this rapidly changing media landscape, the role of the journalist is evolving. Our research examines how professional journalists within a rural community impacted by Hurricane Irene successfully negotiated a new role for themselves, transforming their journalistic practice to serve in a new capacity as leaders of an online volunteer community. We describe an emergent organization of media professionals, citizen journalists, online volunteers, and collaborating journalistic institutions that provided real-time event coverage. In this rural context, where communications infrastructure is relatively uneven, this ad hoc effort bridged gaps in ICT infrastructure to unite its audience. In this paper, we introduce a new perspective for characterizing these information-sharing activities: the “human powered mesh network” extends the concept of a mesh network to include human actors in the movement of information. Our analysis shows how journalists played a key role in this network, and facilitated the movement of information to those who needed it. These findings also note a contrast between how HCI researchers are designing crowdsourcing platforms for news production and how crowdsourcing efforts are forming during disaster events, suggesting an alternative approach to designing for emergent collaborations in this context.

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Acknowledgments

The authors would like to thank all interviewees and their respective organizations; Judy Ramey and Mark Haselkorn for early help in shaping the research design; WGXC for supporting the interview process; Jennifer Turns for help framing the contribution; and the anonymous reviewers for their thoughtful and constructive feedback.

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Correspondence to Dharma Dailey.

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Dailey, D., Starbird, K. Journalists as Crowdsourcerers: Responding to Crisis by Reporting with a Crowd. Comput Supported Coop Work 23, 445–481 (2014). https://doi.org/10.1007/s10606-014-9208-z

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