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Big Data, Big Brother, Big Profit?

Authors: Min Jiang; King-wa Fu;

Big Data, Big Brother, Big Profit?

Abstract

Chinese social media and big data represent an important share of the global Internet, but have received relatively less attention. This editorial examines three dominant discourses based on China’s distinctive and complex political, economic and social realities: “Big Data” (technical focus), “Big Brother” (political focus), and “Big Profit” (economic focus). We argue that the prevailing discourse and practice of big data in China is largely technocentric, decontextualized and nonreflexive, and much less attuned to the social, political, cultural, epistemological, and ethical implications of big data that a human-centric approach would demand. Second, the authoritarian Chinese state poses incredible political challenges to big data research and practice. Third, the practice of Chinese social media and big data is imbued with a discourse of technological nationalism, driven by a handful of monopolistic “national champions.” Despite contention, the state and market players have formed a largely mutually beneficial symbiotic relationship to maximize their political and economic gains. We argue a comparative perspective to foster a global conversation on social media and big data is necessary in order to formulate collective responses to such challenges.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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