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Chinese Perceptions of Threats from the United States and Japan
Author(s) -
Sinkkonen Elina,
Elovainio Marko
Publication year - 2020
Publication title -
political psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.419
H-Index - 95
eISSN - 1467-9221
pISSN - 0162-895X
DOI - 10.1111/pops.12630
Subject(s) - explanatory power , perception , adversary , social psychology , population , psychology , public opinion , politics , perspective (graphical) , mass media , political science , sociology , demography , computer security , philosophy , epistemology , neuroscience , computer science , law , artificial intelligence
People's threat perceptions play a role in influencing foreign policies towards perceived adversary countries. Earlier research has identified multiple components shaping mass‐level threat perceptions including military power, adversary country's perceived intentions, and national identities. On the individual level, education, use of media, and interest in politics have been shown to influence threat perceptions. However, most studies on perceptions of security threats fail to include both contextual and individual‐level explanatory factors and to consider that different national threats may be constructed differently. This research bridges formation of threat perceptions on the individual level to wider societal processes and provides an empirical perspective to understanding threat perceptions among the educated section of the Chinese population. To analyze threat perceptions, students from leading Chinese universities ( N = 771) took part in a survey in the autumn of 2011 and spring of 2012. Respondents who followed conventional media were more likely to perceive both the United States and Japan as threatening, and the effect of media consumption was particularly strong with regards to perceived threat from Japan. In addition, each threat perception was significantly associated with threat‐specific explanatory factors. Potential explanatory factors of threat perceptions were explored with linear regression models.