Urban Region Function Mining Service Based on Social Media Text Analysis

Abstract

Urban region functions are the types of potential activities in an urban region, such as residence, commerce, transportation, entertainment, etc. A service which mines urban region functions is of great value for various applications, including urban planning and transportation management, etc. Many researches have been carried out to dig out different regions' functions, but few researches are based on social media text analysis. Considering that the semantic information embedded in social media texts is very useful to infer an urban region's main functions, we design a service which extracts human activities using Sina Weibo (the largest microblog system in Chinese, similar to Twitter) with location information and further describes a region's main functions with a function vector based on the human activities. Firstly, we predefine a variety of human activities to get the related activities corresponding to each Weibo post using an urban function classification model. Secondly, urban regions' function vectors are generated, with which we can easily do some high-level work such as similar place recommendation. At last, with the function vectors generated, we develop a web application for urban region function querying. We also conduct a case study among the urban regions in Beijing, and the experiment results demonstrate the feasibility of our method.