Social Media and Newsroom Production Decisions

Julia Cagé, Nicolas Hervé, B. Mazoyer
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引用次数: 8

Abstract

Social media affects not only the way we consume news, but also the way news is pro- duced, including by traditional media outlets. In this paper, we study the propagation of information from social media to mainstream media, and investigate whether news ed- itors are influenced in their editorial decisions by stories popularity on social media. To do so, we build a novel dataset including a representative sample of all tweets produced in French between July 2018 and July 2019 (1.8 billion tweets, around 70% of all tweets in French during the period) and the content published online by about 200 mainstream media during the same time period, and develop novel algorithms to identify and link events on social and mainstream media. To isolate the causal impact of popularity, we rely on the structure of the Twitter network and propose a new instrument based on the interaction between measures of user centrality and news pressure at the time of the event. We show that story popularity has a positive effect on media coverage, and that this effect varies depending on media outlets’ characteristics. These findings shed a new light on our understanding of how editors decide on the coverage for stories, and question the welfare effects of social media.
社交媒体和新闻编辑室制作决策
社交媒体不仅影响了我们消费新闻的方式,也影响了新闻的生产方式,包括传统媒体的生产方式。本文研究了信息从社交媒体向主流媒体的传播,并探讨了新闻编辑是否会受到社交媒体上新闻受欢迎程度的影响而做出编辑决策。为此,我们建立了一个新的数据集,其中包括2018年7月至2019年7月期间用法语制作的所有推文(18亿条推文,约占同期所有法语推文的70%)的代表性样本,以及约200家主流媒体在同一时期在线发布的内容,并开发了新的算法来识别和链接社交媒体和主流媒体上的事件。为了分离受欢迎程度的因果影响,我们依靠Twitter网络的结构,并提出了一种基于用户中心性和事件发生时新闻压力之间的相互作用的新工具。我们发现,故事受欢迎程度对媒体报道有积极影响,这种影响因媒体的特点而异。这些发现让我们对编辑如何决定报道内容的理解有了新的认识,并对社交媒体对社会福利的影响提出了质疑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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