基于互联网搜索的住房价格公众关注度：城际网络特征与内在机理

Housing price, which affects the residential housing decision and likelihood of migrating destination choice, not only has become one of the most pressing issues that Chinese urban residents facing， but also has received considerable public attentions in recent years. As the rapid development of Internet technology, the individuals’ behaviors of concerning housing price are changing, and their search activities can be recorded by Web search engines as well. Focusing on the city network of Internet searches-based public attention on housing prices, which has both social and spatial characteristics, has contributed to deepen the understandings of Chinese urban housing problem in the studying framework of “flow-network-interaction”, and further has enriched the theories and empirical cases related to geocyberspace, city network and spatial organization. This study hypothesizes that the public attentions of urban housing in cyberspace as a new form of flow in city network correlates with inter-city attractiveness in geography space. Further, based on conceptual model establishment and data mining, comprehensive approaches of complex network, Geographical Information System and spatial analysis, econometric model and Agent Based Model will be integrated employed to test the basic hypothesis following the logical clue: public attentions’ recognition-networks’ features- inner mechanism-optimization. The expected results of this study are as follows: 1) reveal the characteristics and spatial heterogeneous of inter-city network of public attention on housing price, and further explore to couple and visualize the networks both in cyberspace and geographic space; 2) analyze the inner mechanisms of inter-city public attention on housing price and their networks from the diverse perspectives, which probably contribute to enrich related theories of city network; 3) provide political supports for optimizing the Chinese cities’ spatial organization and coordinating the spatial supply and demand of urban living spaces.

在可支付压力下，城市住房价格是影响居民置业迁居的重要因素，也是最受关注的社会问题之一。互联网搜索为研究住房价格公众关注度提供了新的思路与数据基础。聚焦具有社会-空间双重属性的房价关注度网络，有利于在“流-网络-相互作用”框架下深化对住房问题的理解，推动城市网络与空间组织、赛博地理空间等理论的拓展与实证更新。本研究基于城市住房价格关注度网络特征及其空间异质性是城市间内在吸引力与相互作用外在表征的假设，在概念模型与数据挖掘的基础上，综合采用网络分析、GIS空间分析、计量模型与ABM模拟等方法，按照“关注度识别-网络特征-作用机理-优化调控”的逻辑拟实现以下目标：1)揭示城市住房价格关注度及其网络特征的异质性，实现赛博-地理空间耦合与可视化; 2)从驱动、互动和演化三个层面探索城市住房价格关注度及其网络的内在机理，丰富城市网络及其相关理论; 3)凝练城市空间组织优化与居住空间供需格局调控的策略。

围绕“人—空间关系”这一核心科学问题，以“城市网络”、“城市住房”、“城市土地”、“城市人口活动”切入，探索多尺度下的城市空间网络与关系模式。从主要内容看，具体包括：1)在城际尺度，以互联网搜索为研究住房价格公众关注度提供新的思路与数据基础，聚焦具有“社会—空间”双重属性的房价关注度网络，有利于在“流—相互作用—网络”框架下深化对住房问题的理解，推动城市网络与空间组织、赛博地理空间等理论的拓展与实证更新。此外，作为另外一个尝试，分别从网络整体特征、结构对等性和富人俱乐部现象探索长江中游城市群的CO2 排放网络的复杂性、空间性及其可视化。2)在城市尺度，探索源于互联网的人口活动密度大数据的特征，并分析了城市中心区域周末、工作日不同时点人口活动密度分布的时空特征及异质性，为理解百度热力图在人口活动研究中的潜在价值，并为更好地考虑实时变化的人口活动分布，更加科学、精准地进行城市规划与空间管理提供了支撑。3)在城市社区尺度，选择典型社区，通过实地数据采集与调研，从不同空间尺度与维度分析了社区快递投送点空间分布与空间形态、快递收件人所在地与快递来源地空间网络分布特征；探索互联网经济、网络购物和快递行业的快速发展对于大众消费行为特征的改变，消费过程中人与空间关系的重塑，以及城市社区景观与社会关系模式的变化所带来的影响。