Understanding the effects of the textual complexity on government communication: Insights from China’s online public service platform

While texts are the primary carriers of information for government decision making, few studies have examined the role of textual complexity in government-citizen communication. Using a variety of natural language processing methods, this paper measured textual complexity from the perspectives of word complexity, logical complexity, and abnormal negative emotion based on the textual data of the 1.15 million online messages left by the citizens to government leaders on China’s online public service platform, and explored its impact on government responses. Based on the Double-hurdle model, this paper found that the government response can be composed of two decision-making processes: response-intention, which indicates whether to respond, and response-level, which represents the extent of response. For response-intention decision-making, the simpler the words and logic of the message, the more likely it is to receive a reply from the government. For response-level decision-making, messages with more complex words and logic received a higher level of government response. Abnormal negative emotion in the message significantly reduced the government’s response intention and response level, and the negative effect of abnormal negative emotion on response intention was much greater than on the response level. This study not only helps to understand how the government makes decisions based on textual information, but also has important value for responsive government construction and equalization of government services.