The Institutional Impacts of Algorithmic Distribution: Facebook and the Australian News Media

被引:12
作者
Bailo, Francesco [1 ]
Meese, James [2 ]
Hurcombe, Edward [2 ]
机构
[1] Univ Technol Sydney, Sydney, NSW, Australia
[2] RMIT Univ, Melbourne, Vic, Australia
来源
SOCIAL MEDIA + SOCIETY | 2021年 / 7卷 / 02期
基金
澳大利亚研究理事会;
关键词
Facebook; algorithm; journalism; distribution; news; Australia; SOCIAL MEDIA; WEB ANALYTICS; JOURNALISM; TWEET;
D O I
10.1177/20563051211024963
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
Since changing its algorithm in January 2018 to boost the content of family and friends over other content (including news), Facebook has signaled that it is less interested in news. However, the field is still trying to understand the long-term impacts of this change for news publishers. This is a problem because policymakers and legislators across the world are becoming concerned about the relationship between platforms and publishers. In particular, there are worries that platforms' ability 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 to 2020, with a particular focus on the January 2018 algorithm change. We do this by analyzing Facebook data (2,082,804 posts from CrowdTangle) and external traffic data from 32 major Australian news outlets. These data are contextualized 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 contextualize with industry reportage. However, the data provide vital longitudinal insights into the performance and responses of individual media outlets, news categories, and the Australian media sector as a whole during a critical moment of algorithmic change.
引用
收藏
页数:13
相关论文
共 52 条
[1]   VIRAL NEWS ON SOCIAL MEDIA [J].
Al-Rawi, Ahmed .
DIGITAL JOURNALISM, 2019, 7 (01) :63-79
[2]   Between creative and quantified audiences: Web metrics and changing patterns of newswork in local US newsrooms [J].
Anderson, C. W. .
JOURNALISM, 2011, 12 (05) :550-566
[3]  
[Anonymous], 2018, DIG PLATF INQ PREL R
[4]   Historical Institutionalism in Communication Studies [J].
Bannerman, Sara ;
Haggart, Blayne .
COMMUNICATION THEORY, 2015, 25 (01) :1-22
[5]   Shares, Pins, and Tweets News readership from daily papers to social media [J].
Bastos, Marco Toledo .
JOURNALISM STUDIES, 2015, 16 (03) :305-325
[6]  
Bell EJ., 2017, PLATFORM PRESS SILIC
[7]  
Bell K., 2021, ENGADGET
[8]  
Benkler Yochai Robert, 2018, NETWORK PROPAGANDA M, DOI [DOI 10.1093/OSO/9780190923624.001.0001, DOI 10.1093/OSO/9780190923624.003.0010]
[9]   CRITICAL QUESTIONS FOR BIG DATA Provocations for a cultural, technological, and scholarly phenomenon [J].
Boyd, Danah ;
Crawford, Kate .
INFORMATION COMMUNICATION & SOCIETY, 2012, 15 (05) :662-679
[10]   Management and resistance in the digital newsroom [J].
Bunce, Mel .
JOURNALISM, 2019, 20 (07) :890-905