Computing traffic congestion degree using SNS-based graph structure
Putu Y. Kusmawan, Bonghee Hong, Seungwoo Jeon, Jiwan Lee, Joonho Kwon · 2014
Social networking site (SNS) messages can contain subjective traffic information, including congestion-related expressions such as “bad traffic” or “traffic is crazy”. Moreover, they also contain heterogeneous levels of location information, such as a point (latitude, longitude), a road, or an area name, which complicates the process of collecting related traffic information. This paper aims to use SNS messages for monitoring traffic conditions on a road by computing the traffic congestion degree. The process begins by classifying those SNS messages that are related to a road in terms of location information and constructing an initial graph structure to store each message. Because of the heterogeneous location types, we need to combine the initial graph structures based on their spatial references. We can then measure the subjective congestion by computing an expression score using our rule-based approach.