2025 VOLUME 5 ISSUE 2
RESEARCH ARTICLE
Exploring online government-citizen interaction from a responsive government perspective with a text mining method
AUTHOR
Fang Wang, Wenjing Sun, Rujing Yao
ABSTRACT
With the growth of online interaction between the government and citizens, various platforms have accumulated a vast amount of data that contain rich public demands and diverse public opinions, with important value for improving public services. This study conducted an in-depth analysis of the data on the DL sector of a national platform for government-citizen interaction in China, the Message Board for Leaders on the People's Daily Online. First, the LDA was used to mine the topics of public messages. Second, a sentiment lexicon was tailored to analyze the sentiment in public messages and government responses. Third, three indicators, i.e., attitude, timeliness, and usefulness, were selected to assess the effectiveness of government responses. Then the influence of public messages on government responses was explored. It was found that the topic of public messages significantly affects the attitude and timeliness of government responses, but does not significantly affect their usefulness; the sentiment expressed in public messages affects that of government responses; and the topics living environment and demolishing illegal construction attract the most public attention. Finally, several suggestions for improving public service were proposed.
KEYWORDS
Online government-citizen interaction; LDA topic model; Responsive government; Sentiment analysis; Public message; Government responses
