Research on the Effect of Government Responsiveness of The Chinese E-Government—Based on the Local Leader Message Board (LLMB) Data of RenMinWang Website

Ru-min LYU, Shu-liang ZHAO


Based on the data collected from the Chinese most authoritative website RenMinWang(人民网, a national website of China official media)’s forum Local Leaders Message Board (LLMB), using logistic regression model, the author analysis 100788 appeal texts on LLMB, covered 30 Chinese provinces. This paper use Big Data and text mining method to analysis the influencing factors of the satisfaction on the interaction between government and netizen. The empirical results show that: the efficiency of government responsiveness significantly improves netizen's satisfaction. In the government response text, the higher the policy complexity is, the lower satisfaction it will get from the netizen. The network interaction between the government and the netizen meets the expectation-value theory. The netizen’s appeal to the Chinese provincial leaders will get a lower satisfaction level of the government’s response, it maybe caused by their appeal’s complexity of solving. Also if the government response text are to long, and if there are more policy and laws, it will get a lower probability of satisfaction.


Network Interaction of Politics, Government Responsiveness, Text Mining


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