Replication Data for: The institutional impacts of algorithmic distribution: Facebook and the Australian news media

Replication notes To replicate the analysis refer to replication_code.pdf; replication_code.Rmd. Paper abstract Since changing its algorithm in January 2018 to boost the content of family and friends over other content (including news), Facebook has signalled that it is less interested in news. The long-term impacts of this change for news publishers is still unclear. This is a problem because policymakers and legislators across the world are concerned about the relationship between platforms and publishers. In particular, they are worried that the ability of platforms to make unilateral decisions about how their algorithms operate may harm the economic sustainability of journalism. This article provides some clarity around the relationship between these two parties through a longitudinal study of the Australian news media sector’s relationship with Facebook from 2014 – 2020, with a particular focus on the January 2018 algorithm change. We analyse Facebook data (2,082,804 posts from CrowdTangle) and external traffic data from 32 major Australian news outlets. This data is contextualised by additional desk research. We identify a range of trends including the decline of news sharing, the collapse in the performance of ‘social news’, the variable position of social media as a source of referral traffic and most critically, the diffused nature of the 2018 algorithm change. Our approach cannot make direct causal inferences. We can only identify trends in on-platform performance and referral traffic, which we then contextualise with industry reportage. However, the data provides vital longitudinal insights into the performance and responses of individual media outlets, news categories and the Australian media sector as a whole.

复现说明：若需复现本分析，请参考复现代码文件replication_code.pdf与replication_code.Rmd。
论文摘要：自2018年1月调整算法以优先展示亲友内容而非其他内容（含新闻内容）以来，脸书（Facebook）已明确表示其对新闻内容的关注度有所降低。此次调整对新闻出版商的长期影响仍不明朗。这一现状存在隐患，因为全球各国的政策制定者与立法者均对平台与出版商之间的关系感到担忧。具体而言，他们担忧平台可单方面决定算法运行规则的这一特性，可能损害新闻业的经济可持续性。
本文通过对2014年至2020年澳大利亚新闻媒体行业与脸书（Facebook）的关系开展纵向研究，并重点聚焦2018年1月的算法调整，为厘清双方之间的关系提供了新的视角。本研究分析了来自CrowdTangle的脸书平台数据（共2082804条帖子）以及澳大利亚32家主流新闻机构的外部流量数据，并辅以案头研究为上述数据提供背景支撑。本研究识别出一系列趋势，包括新闻分享量的下滑、「社交新闻」传播效果的崩塌、社交媒体作为引荐流量来源的地位波动，以及最为关键的2018年算法调整的弥散性特征。本研究方法无法直接得出因果推论，仅能识别平台内表现与引荐流量的相关趋势，并结合行业报道为这些趋势补充背景信息。但本研究数据仍为各媒体机构、新闻品类以及澳大利亚整体媒体行业的表现与应对举措提供了极具价值的纵向视角。