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We describe our analysis of three months worth of collected human-physical environment interactions (foursquare check-in) data for two European cities: a medium-sized city in the Mediterranean and a larger city in North West Europe. Our analysis shows that though the data generated by the citizens is scarce (i.e. on average less than 15 users checked in at any time during the day), nevertheless they...
In this paper, we proposed a novel scheme to infer user's location using microblog text and friendships, without known geo information. The major part of our research is identifying local words, words that associated with some particular location. With local words we identified, we use conditional random fields (CRF), to detect location specific microblog. Then we can estimate the most possible location...
In this paper, we provide a detailed analysis on the venue popularity in Foursquare, a leading location-based social network. By collecting 2.4 million venues from 14 geographic regions all over the world, we study the common characteristics of popular venues, and make the following observations. First, venues with more complete profile information are more likely to be popular. Second, venues in...
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