Measuring Crowd-sourced Cognitive Distance between Urban Clusters with Twitter for Socio-cognitive Map Generation
Measuring Crowd-sourced Cognitive Distance between Urban Clusters with Twitter for Socio-cognitive Map Generation
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发表时间：
2012
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通讯作者：
Shoko Wakamiya;Ryong Lee;K. Sumiya
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作者：
Shoko Wakamiya;Ryong Lee;K. Sumiya
在进行基于位置的决策时，人们往往依赖于对真实的空间的地理空间认知，而不是真实的世界中的确切物理距离。事实上，基于人们地理空间认知的距离在城市生活的许多方面都是有用的。在本文中，我们测量心理接近的城市地区借用人群的经验，很容易从基于位置的社交网络。特别是，我们提出了一种方法来衡量城市地区之间的社会认知距离，通过监测人群的流动性，使用地理标记的Twitter上的推文。特别是，为了直观和简单地表示城市地区之间的认知距离，我们生成一个社会认知地图变形的城市地区的拓扑结构的基础上测量的认知距离MDS（多维缩放）。在实验中，我们展示了一个社会认知地图所产生的人群的运动为基础的城市地区的关系与大量的地理标记的推文从Twitter。
When conducting location-based decision makings, people often rely on geospatial cognition to the real space than the exact physical distance in the real world. In fact, distance based on people’s geospatial cognition is useful in many respects of urban life. In this paper, we measure psychological proximity of urban areas by borrowing crowd’s experiences easily available from location-based social networks. In particular, we propose a method to measure socio-cognitive distance between urban areas by monitoring crowd’s mobility using geo-tagged tweets on Twitter. In particular, in order to intuitively and simply represent cognitive distance between urban areas, we generate a socio-cognitive map by deforming a topology of urban areas based on the measured cognitive distance with MDS (Multi-Dimensional Scaling). In the experiment, we show a sociocognitive map generated by crowd’s movements based urban area relations with massive number of geo-tagged tweets from Twitter.