Please use this identifier to cite or link to this item: https://doi.org/10.1080/17544750.2020.1830422
Title: Traffic media: How algorithmic imaginations and practices change content production
Authors: Weiyu Zhang 
Zhuo Chen
Yipeng Xi
Keywords: Agency
algorithm
big data
independent content providers
platform
power
Issue Date: 12-Oct-2020
Publisher: Taylor & Francis
Citation: Weiyu Zhang, Zhuo Chen, Yipeng Xi (2020-10-12). Traffic media: How algorithmic imaginations and practices change content production. Chinese Journal of Communication 14 (1) : 58-74. ScholarBank@NUS Repository. https://doi.org/10.1080/17544750.2020.1830422
Abstract: This study aims to explore the algorithmic imaginations and related practices of China’s independent content providers by situating them in the interaction network in relation to other actors, including algorithms, platforms, peers, and legacy media professionals. Semi-structured interviews were conducted with 23 informants who were experienced in traffic media, which are new media platforms that rely on traffic as their business model and control traffic through algorithmic technologies and policies. Through contrasting independent content creators to legacy media professionals and platform employees, the analysis showed that the content providers shared the normative expectation that algorithms should direct traffic based on their content although they were usually surprised or disappointed. They considered that the function of algorithms was a classifying and disciplining mechanism that exerted power through the distribution of traffic. They chose to “play with” or “please” algorithms by using individual or collective tactics. The relationships between their imaginations and their agency, as well as the fundamental limitations imposed by the Chinese state, are also discussed. An era of traffic media is argued to have emerged, and the network of power relations has evolved.
Source Title: Chinese Journal of Communication
URI: https://scholarbank.nus.edu.sg/handle/10635/187281
ISSN: 1754-4750
DOI: 10.1080/17544750.2020.1830422
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