The clues in the news media coverage: detecting Chinese collective action trend from a text analytics research framework

Li Ying, Li Linlin and Li Qianqian ()
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Li Ying: Jilin University
Li Linlin: Jilin University
Li Qianqian: Chinese Academy of Sciences

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 2, No 17, 729-749

Abstract: Abstract With the adjustment of social relations and interest patterns brought about by the comprehensive deepening reform in China, new and old contradictions are intertwined, various risks are increased, collective actions occasionally occur, and some new trends are observed. However, due to there is no authoritative database of collective action in China, it is difficult to observe the trend of collective actions. There has been significant research show that news coverage is an effective way to obtain collective action information. Thus, we examine the recent news coverage shift in terms of collective action. We collected 5354 news coverages from 2014 to 2018. Then, we constructed a collective action domain-specific word dictionary and presented a method to automatically detect temporal, spatial, and topical trends of collective action. The proposed framework is based on text mining analysis that collects data from news outlets and extracts valuable data for perceiving the collective action trends. The results show that the proposed method is an effective tool to identify the trends in collective action via machine learning.

Keywords: News coverage; Collective action; Text mining; Cluster analysis; Topic analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11135-021-01137-3

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