The national geographic characteristics of online public opinion propagation in China based on WeChat network
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Abstract
Offline networks have been the subject of intense academic scrutiny for many decades, but we still know little about the nationwide spatial interaction patterns and its application for public opinion management of online social networks. With the aim of uncovering the geographic interaction characteristics of online public opinion propagation, we analyze a large dataset obtained from WeChat, the most popular social media application in China, and construct the spatial interaction network G, which contains 359 city-nodes. It is found that the communities in the network and the administrative division corresponded well with each other, and cities with high betweenness and degree also develop well in the economy. Public opinion propagation depends on the state of online interaction. The findings indicate that public opinion should be managed separately by regions divided according to the community division, and different regions should adopt different management methods according to their economic, historical and political characteristics. In our work, the possibility and opportunity is presented to study the spatial interaction patterns of online public opinion propagation with the massive behavioral data and the methods of complex network.
Keywords
Online interaction network Public opinion online Community detection Regional characteristicsNotes
Acknowledgements
This study is supported by National Key Research & Development (R&D) Plan under Grant No. 2017YFC0803300 and the National Natural Science Foundation of China under Grant Nos. 71673292,61503402 and Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion. We also thank Fibonacci Consulting Co. Ltd. for the big dataset
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