基于微博的西安市交通拥堵状况时空分布研究

Study on spatio-temporal distribution of Xi′an traffic congestion based on micro-blog

通过自主开发的数据抓取软件获得西安市新浪微博数据,利用文本分析筛选出表达交通拥堵的微博数据,通过多时间尺度分析,得到交通拥堵的月、周内和日分布规律;经过ArcGIS 10.2的点密度分析工具计算及可视化处理,得到交通拥堵的空间分布规律。结果表明:在时间上,交通拥堵与居民工作日通勤、节假日外出等有密切联系;在空间上,交通拥堵与商业区、学校等人流量密集区域等因素有密切关系。研究证明了利用社交媒体数据研究城市交通拥堵问题的可行性。

Sina micro-blog data of Xi＇an city in the past year was obtained by self-developed data ripping software, and the micro-blog data that expressing traffic congestion was selected by text analysis. Through multiple time scales analysis, the distribution of traffic congestion in the month, week and day were obtained. By using dot density analysis tool and visual processing in ArcGIS 10.2, the spatial distribution of traffic jams were obtained. The results show that, in time scales traffic congestion has the closest connection with residents weekday commuting, holiday travelling, etc. and in space scales, traffic congestion has the closest connection with commercial areas, schools and other high traffic density areas. The study proved that the feasibility of using social media data to study the urban traffic congestion.