Bulletin of Chinese Academy of Sciences (Chinese Version)
Keywords
Belt and Road; individualism; trust; social media
Document Type
Article
Abstract
It has been highly stressed that national characters play a critical role in regional cooperation across "Belt and Road" countries or areas. However, the traditional method is often unworkable, because of the vast territory, multiple nations, and the complexity of geopolitics, economics, and cultural traditions along "Belt and Road". From the perspective of cultural psychology and big data analytics, the present research was an attempt to explore cultural and cooperative patterns along "Belt and Road", using the individualism index (independent vs.interdependent self construal) based on the Twitter dataset and the prediction model of social trust (generalized vs. particularized). The results show that there are big differences in individualism among "Belt and Road" countries or areas, which are mainly explained by the variation of their colonial histories and religious traditions. Furthermore, generalized trust (related to strangers and foreigners) and particularized trust (related to family and acquaintances) are found to be significantly predicted by individualism on Twitter. In conclusion, the current findings demonstrate the cultural diversity of self construal and social trust across "Belt and Road" countries or areas, suggesting that the new approach based on social media should be concerned in exploring national characters and behavioral patters in this regional cooperation.
First page
298
Last Page
307
Language
Chinese
Publisher
Bulletin of Chinese Academy of Sciences
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Recommended Citation
Michel Shengtao, WU; Yang, ZHOU; Xiaolan, FU; Xiaoqian, LIU; Tianli, LIU; and Tingshao, ZHU
(2018)
"Identifying Culture and Cooperative Behavior Pattern in Belt and Road Area: Psychological Analysis of Big Data on Twitter,"
Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 33
:
Iss.
3
, Article 10.
DOI: https://doi.org/10.16418/j.issn.1000-3045.2018.03.010
Available at:
https://bulletinofcas.researchcommons.org/journal/vol33/iss3/10