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e accelerating urbanization procedure is pu ing increasing pres- sure on the management of cities. e administrative zones by which a city is managed are setup based on historical or political reasons, while the dynamics of people is hardly considered in the context. We exploit the widely available mobility data to divide the urban areas into zones by the joint K-mean clustering in origin and destination...
People generate online content everyday at every hour at social networks. Social networks are a medium in which people can give their opinion on different topics and obtain new information. The content people create can be useful for researchers to understand human behavior in cities such as Quito. In this work, we are going to describe how Quito city is described on the travel network TripAdvisor...
Cities are complex systems evolving constantly. Thus, it is necessary to improve the way we collect intra-urban data in order to quantify such evolution. We propose a methodology to transform geo-located tweets into labels for different areas of a given city using DBPedia, Wikipedia and Foursquare categories. We conduct experiments using 77K geolocated tweets posted in Milan during November and December...
Nowadays, detecting health-violating restaurants is a serious problem due to the limited number of health inspectors in a city as compared to the number of restaurants. Rarely inspectors are helped by formal complains, but many complaints are reported as reviews on social media such as Yelp. In this paper we propose new predictors to detect health-violating restaurants based on restaurant sub-area...
We address a problem of extracting functionally similar regions in urban streets regarded as spatial networks. Such characteristics of regions will play important roles for developing and planning city promotion, travel tours and so on, as well as understanding and improving the usage of urban streets. In order to analyze such functionally similar regions, we propose an acceleration method of the...
The opinion leaders play an important role in the process of network public opinion spreading. In order to quickly and efficiently discover the opinion leaders, this paper analyzes the characteristics of complex networks in social networks and proposes density-based spatial clustering of applications with noise algorithm based on local community detection method. With Sina micro-blog user as the research...
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