Name
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1140/epjds/s13688-019-0187-7 | EPJ Data Science |
Keywords | Field | DocType |
Mobile phone graph, Mobile social groups, Quasi-clique, Group points of interest, City’s points of interest | Social group,Urban space,Data science,Text message,Internet privacy,Leverage (finance),Computer science,Footprint,Mobile phone,Metropolitan area,The Internet | Journal |
Volume | Issue | ISSN |
8 | 1 | 2193-1127 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Zignani | 1 | 85 | 13.07 |
| Christian Quadri | 2 | 27 | 7.96 |
| Sabrina Gaito | 3 | 209 | 29.64 |
| Gian Paolo Rossi | 4 | 390 | 78.09 |