Measuring Crowd-sourced Cognitive Distance between Urban Clusters with Twitter for Socio-cognitive Map Generation

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.