社会化媒体
游戏娱乐
背景(考古学)
新闻
广告
新闻媒体
政治
动作(物理)
公共关系
生产(经济)
政治学
社会学
计算机科学
业务
万维网
地理
物理
考古
量子力学
法学
经济
宏观经济学
作者
Subhayan Mukerjee,Yang Tian,Yilang Peng
摘要
Abstract Social media metrics allow media outlets to get a granular, real-time understanding of audience preferences, and may therefore be used to decide what content to prioritize in the future. We test this mechanism in the context of Facebook, by using topic modeling and longitudinal data analysis on a large dataset comprising all posts published by major media outlets used by American citizens (N≈2.23M, 2015–2019). We find that while the overall effect of audience engagement on future news coverage is significant, there is substantial heterogeneity in how individual outlets respond to different kinds of topics. A handful of right-wing media outlets are more likely to respond to audience engagement metrics than other outlets, but with partisan politics topics and not with entertainment-oriented content. Our research sheds new light on how social media platforms have shaped journalistic practices and has implications for the future health of journalism in the United States.
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