Understanding how the expression of online citizen petitions influences the government responses in China: An empirical study with automatic text analytics

Online participation is an important tool for citizens to express their demands, and it is essential for government agencies to respond to public petitions on time and effectively. However, few studies have focused on the rich textual characteristics within the expression of citizen petitions and the effects on the efficiency of government responses as well as response outcomes. In this study, we construct a theoretical model to explain how sentiments, fields, and detailed contents of online petitions influence the timeliness and text length of the corresponding government responses on the basis of discourse theory and government pressure theory. Using the data on the online petition platform of one provincial government in China, textual features are automatically extracted through text analysis techniques. Multiple regression models are employed with a heterogeneity analysis to examine the model. The results show that more negative sentiments, public interest, and detailed contents in the petitions will impede the timeliness of the corresponding responses and bring about longer responses since such petitions are usually complex and hard to address. These findings help better understand the hidden mechanisms of the interaction between governments and citizens, providing theoretical and practical implications.