Abstract
Government and market are the two main factors that drive the practices of the Chinese media system and influence the news construction process. A dramatic, socially disruptive event like the 2014 Kunming terrorist attack has the potential both to damage the government image and to attract readers. Analyzing how different types of media, more specifically the state-sponsored and the market-oriented press, construct a terrorist attack may therefore reveal essential characteristics of the Chinese media system and its relationship with both government and market. In doing so, the present study makes a contribution in terms of methodology, resources, and empirical description. From a methodological perspective, drawing on a dataset of 275 news articles about the Kunming attack that was collected from 16 mainstream Chinese newspapers, we explore the possibilities of combining computer-assisted techniques (i.e. part-of-speech tagging, sentiment analysis, collocation, and concordance) and Discursive News Values Analysis (DNVA), based on which we identified 699 Chinese lexical indicators distributed across ten news values. The open-source wordlist produced by this procedure will facilitate future quantitative DNVA, but also fills a resource gap in non-English news values studies. After calculating the mean normalized frequency of indicators under each news value on a more empirical level, we found that the state-sponsored and the market-oriented press converge in foregrounding the news values of Eliteness and Personalization, in line with public expectations, while at the same time diverging in their use of the news values of Positivity, Negativity, and Superlativeness, which we can relate to the different aims and responsibilities of these two types of newspapers.
Original language | English |
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Article number | 100578 |
Pages (from-to) | 1-14 |
Number of pages | 14 |
Journal | Discourse, Context & Media |
Volume | 45 |
DOIs | |
Publication status | Published - Mar 2022 |
Bibliographical note
Funding Information:This work was supported by the China Scholarship Council [Ph.D. Fellowship: 201708410116 and 201606010359]. Furthermore, we are grateful to the Dynamic Circulation Corpus (DCC) developed by Beijing Language and Culture University for supporting the data in this paper.
Publisher Copyright:
© 2022 Elsevier Ltd
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Chinese Lexical Indicators of News Values (LINV)
Guo, J. (Creator), Mast, J. (Supervisor) & Vosters, R. (Supervisor), Zenodo, 2025
Dataset