新闻来源发现:支持用户生成内容中新闻来源的识别

Yixue Wang, N. Diakopoulos
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引用次数: 12

摘要

许多记者和新闻编辑室现在通过利用用户生成内容(UGC)将受众贡献纳入其采购实践。然而,他们在向教资会寻求信息时的采购需求和做法仍然没有被研究人员深刻理解,也没有得到工具的充分支持。本文首先报告了对九名专业记者进行的关于他们的UGC来源实践的定性访谈研究的结果,详细说明了记者通常在教资会中寻找什么,并详细阐述了两种UGC来源方法:深度报道和广泛报道。这些发现为我们提供了一个以人为本的设计方法,为记者提供UGC来源工具的原型,使记者能够根据用户的示例内容交互式地过滤和排名UGC。我们与9位在日常工作中获取教资会内容的专业记者一起评估了这个原型,以了解如何启用和转变教资会内容的获取实践,同时也发现了未来研究和设计的机会,以支持新闻的获取实践和意义生成过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Journalistic Source Discovery: Supporting The Identification of News Sources in User Generated Content
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 first 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 findings then inform a human-centered design approach to prototype a UGC sourcing tool for journalists, which enables journalists to interactively filter 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.
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