Mining Newsworthy Events in the Traffic Accident Domain from Chinese Microblog
Mining Newsworthy Events in the Traffic Accident Domain from Chinese Microblog
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DOI：
10.1142/s021962201950010x
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发表时间：
2019-03
期刊：
影响因子：
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通讯作者：
Xiangling Fu;Jintae Lee;Chenwei Yan;Li Gao
中科院分区：
文献类型：
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作者：
Xiangling Fu;Jintae Lee;Chenwei Yan;Li Gao
微博可以为记者提供一个宝贵的资源，因为它捕捉潜在的新闻价值的事件，因为他们发生，包括远程发生的。鉴于典型微博的巨大容量和快速节奏，监控所有微博帖子以发现潜在的新闻事件是不切实际的。因此，如果存在一种使用文本挖掘来帮助识别此类事件的方法，则会非常有用。奋进，我们需要一个好的新闻价值模型，而且可以用文本挖掘技术来操作。本研究首先采用了最具综合性和被广泛接受的Shoemaker新闻价值模型，并在对中国新闻媒体领域专家和用户进行广泛访谈的基础上对该模型进行了提炼，然后将其应用于交通事故领域的文本分析，最后将其应用于交通事故领域的新闻报道中，以验证该模型的可行性和实用性。并以中国最大的微博网站--微博为例，验证了该方法的可行性和有效性。因此，我们认为，这项研究通过开发和测试迄今为止最全面和可计算的新闻价值模型，在理论和方法上做出了重要贡献。最后指出了其局限性和需要进一步研究的领域。
Microblog can provide a valuable resource for journalists as it captures potential newsworthy events as they occur, including ones occurring remotely. Given the large volume and the fast pace of typical microblog, it is impractical to monitor all microblog postings for potential news events. Therefore, it would be useful if a method exists that uses text mining to help identify such events. For this endeavor, we need a good model of newsworthiness that furthermore can be operationalized with text-mining techniques. This study examines the feasibility and usefulness of such a model by first adopting the Shoemaker model of newsworthiness, one of the most comprehensive and accepted among such models; refining it based on a set of extensive interviews with domain experts and users in the context of news media in China; operationalizing it with a set of text-analytic measures in the domain of traffic accident; and testing its feasibility and validity using data from Weibo, the largest microblog site in China. As such, we believe that this study makes important theoretical and methodological contributions by developing and testing the most comprehensive and computable model of newsworthiness to date. We also point out its limitations and the areas that need further research.