Abstract
The tendency of people to form socially cohesive groups that get together in urban spaces is a fundamental process that drives the formation of the social structure of cities. However, the challenge of collecting and mining large-scale data able to unveil both the social and the mobility patterns of people has left many questions about urban social groups largely unresolved. We leverage an anonymized mobile phone dataset, based on Call Detail Records (CDRs), which integrates the usual voice call data with text message and Internet activity information of one million mobile subscribers in the metropolitan area of Milan to investigate how the members of social groups interact and meet onto the urban space. We unveil the nature of these groups through an extensive analysis, along with proposing a methodology for their identification. The findings of this study concern the social group behavior, their structure (size and membership) and their root in the territory (locations and visit patterns). Specifically, the footprint of urban groups is made up by a few visited locations only; which are regularly visited by the groups. Moreover, the analysis of the interaction patterns shows that urban groups need to combine frequent on-phone interactions with gatherings in such locations. Finally, we investigate how their preferences impact the city of Milan telling us which areas encourage group get-togethers best.
Highlights
The understanding of tight-knit social groups represents a key factor in the development of services which integrate contextual information from social and mobility data sources [1]
By applying the above procedure, we analyze how urban groups meet and behave within the urban space. We show that these groups meet all the main criteria of what makes for a sociological group, namely: mutuality; reachability; interactivity
The results show the existence of a bias among the members taking part in urban group gatherings: there is a subset of members who take part frequently in the get-togethers, while another subset of members who are less involved in the group’s face-to-face interactions
Summary
The understanding of tight-knit social groups represents a key factor in the development of services which integrate contextual information from social and mobility data sources [1]. Our analysis rests on an anonymized mobile phone dataset based on Call Detail Records (CDRs) over a span of 67 days that integrate the usual voice call data with text message and Internet activity information of one million mobile subscribers in the metropolitan area of Milan This wealth of data provides us with a unique opportunity to study how social groups interact and meet in an urban space having a large population. Combining quite a precise positioning of the customers with their on-phone relationships, our mobile phone data enable us to identify and characterize cohesive groups that couple strong on-phone interactions with the attitude to share specific urban places where they co-locate to perform various social activities, e.g. family-, work- and leisure-oriented ones and/or participatory events. The interaction graph is the input of the stage which identifies cohesive groups
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