Linguistic Dynamic Analysis of Traffic Flow Based on Social Media—A Case Study

In China, the traffic police's micro-bo provides instant information for travelers and helps drivers to avoid congested roads. Management rules and laws, which are compatible with the traffic situation, help to maintain the road traffic order, improve traffic flow smoothness, and prevent traffic-related accidents. Formulating reasonable rules and laws is the key to traffic management. Furthermore, the analysis of traffic flow is good for the formulation of traffic laws and rules. In this paper, the congestion time, congested place, and congestion reason are analyzed on the traffic police's micro-bo, and the theories of linguistic dynamic systems based on multifactor time-varying universe and fuzzy comprehension evaluation are used to analyze traffic flow. In addition, dynamic fuzzy rules on time-varying universe are built to provide the corresponding traffic management rules. As an example, Shenzhen's traffic police micro-bo is used to study the information of traffic congestion, including jam session, congestion location and reasons, and disposal methods, and these results are presented by language form, i.e., keywords walls, and then the linguistic dynamic evolutionary process of working day congestion positions from January to April. Finally, the traffic flow during Labor Day is discussed. The analysis results show that jam sessions, congestion locations and reasons, and disposal methods are very different between working day congestion and holiday congestion.