News journalism has evolved from traditional print media to social media, with a large proportion of readers consuming their news via digital means. Through an analysis of over 1.3 million posts across three social media platforms (Facebook, Twitter, Reddit) pertaining to the 2022 U.S. Midterm Elections, this analysis examines the difference in sharing patterns for four types of news sites—Real News, Local News, Low Credibility News, and Pink Slime. Through Platform-Based Analysis, this study observes that users across all platforms share Real and Local News sequentially, and Real News and Low Credibility News sequentially. Through News Type-Based Analysis, this study establishes a Relative Engagement metric, demonstrating a widely varied engagement among the news types. Real News receive the least engagement (defined as the ratio of number of likes a post has vs. the number of followers of the page), while users engage with Pink Slime news the most. Furthermore, this study finds that the sharing of automated local news reporting sites (Pink Slime sites) are divided on political lines. Finally, through a User-Based Analysis, this study finds that automated bot users share a larger proportion of Pink Slime and Low Credibility News, while human users generally share content relating to local communities.

中文翻译：

---

分享什么新闻、在哪里以及如何分享：对 2022 年美国中期选举期间分享的新闻的多平台分析

新闻报道已经从传统的印刷媒体发展到社交媒体，很大一部分读者通过数字方式消费新闻。通过对三个社交媒体平台（Facebook、Twitter、Reddit）上超过 130 万条与 2022 年美国中期选举相关的帖子进行分析，该分析考察了四种类型新闻网站（真实新闻、本地新闻、低新闻）分享模式的差异可信度新闻和粉红史莱姆。通过基于平台的分析，本研究观察到所有平台上的用户依次分享真实新闻和本地新闻，以及真实新闻和低可信度新闻。通过基于新闻类型的分析，本研究建立了相对参与度指标，展示了新闻类型之间广泛不同的参与度。真实新闻的参与度最低（定义为帖子的点赞数量与页面关注者数量的比率），而用户对粉红史莱姆新闻的参与度最高。此外，本研究发现，自动本地新闻报道网站（粉红史莱姆网站）的共享存在政治分歧。最后，通过基于用户的分析，本研究发现自动化机器人用户分享粉红史莱姆和低可信度新闻的比例较大，而人类用户通常分享与当地社区相关的内容。