Many journalists and newsrooms now incorporate audience contributions in their sourcing practices by leveraging user-generated content (UGC). However, their sourcing needs and practices as they seek information from UGCs are still not deeply understood by researchers or well-supported in tools. This paper frst reports the results of a qualitative interview study with nine professional journalists about their UGC sourcing practices, detailing what journalists typically look for in UGCs and elaborating on two UGC sourcing approaches: deep reporting and wide reporting. These fndings then inform a human-centered design approach to prototype a UGC sourcing tool for journalists, which enables journalists to interactively flter and rank UGCs based on users' example content. We evaluate the prototype with nine professional journalists who source UGCs in their daily routines to understand how UGC sourcing practices are enabled and transformed, while also uncovering opportunities for future research and design to support journalistic sourcing practices and sensemaking processes.
CITATION STYLE
Wang, Y., & Diakopoulos, N. (2021). Journalistic source discovery: Supporting the identification of news sources in user generated content. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3411764.3445266
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