A large-scale study of the evolution of web pages
WWW '03 Proceedings of the 12th international conference on World Wide Web
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Heider vs simmel: emergent features in dynamic structures
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
Find me if you can: improving geographical prediction with social and spatial proximity
Proceedings of the 19th international conference on World wide web
Hermes: clustering users in large-scale e-mail services
Proceedings of the 1st ACM symposium on Cloud computing
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
The little engine(s) that could: scaling online social networks
Proceedings of the ACM SIGCOMM 2010 conference
Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
Exploiting locality of interest in online social networks
Proceedings of the 6th International COnference
Exploiting place features in link prediction on location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
TailGate: handling long-tail content with a little help from friends
Proceedings of the 21st international conference on World Wide Web
Routing of multipoint connections
IEEE Journal on Selected Areas in Communications
Ego network models for Future Internet social networking environments
Computer Communications
Detecting tip spam in location-based social networks
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Modeling/predicting the evolution trend of osn-based applications
Proceedings of the 22nd international conference on World Wide Web
Modeling/predicting the evolution trend of osn-based applications
Proceedings of the 22nd international conference on World Wide Web
Active tracking in mobile networks: An in-depth view
Computer Networks: The International Journal of Computer and Telecommunications Networking
Improving augmented reality using recommender systems
Proceedings of the 7th ACM conference on Recommender systems
We know how you live: exploring the spectrum of urban lifestyles
Proceedings of the first ACM conference on Online social networks
On the validity of geosocial mobility traces
Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks
Understanding the locality effect in Twitter: measurement and analysis
Personal and Ubiquitous Computing
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Connections established by users of online social networks are influenced by mechanisms such as preferential attachment and triadic closure. Yet, recent research has found that geographic factors also constrain users: spatial proximity fosters the creation of online social ties. While the effect of space might need to be incorporated to these social mechanisms, it is not clear to which extent this is true and in which way this is best achieved. To address these questions, we present a measurement study of the temporal evolution of an online location-based social network. We have collected longitudinal traces over 4 months, including information about when social links are created and which places are visited by users, as revealed by their mobile check-ins. Thanks to this fine-grained temporal information, we test and compare whether different probabilistic models can explain the observed data adopting an approach based on likelihood estimation, quantitatively comparing their statistical power to reproduce real events. We demonstrate that geographic distance plays an important role in the creation of new social connections: node degree and spatial distance can be combined in a gravitational attachment process that reproduces real traces. Instead, we find that links arising because of triadic closure, where users form new ties with friends of existing friends, and because of common focus, where connections arise among users visiting the same place, appear to be mainly driven by social factors. We exploit our findings to describe a new model of network growth that combines spatial and social factors. We extensively evaluate our model and its variations, demonstrating that it is able to reproduce the social and spatial properties observed in our traces. Our results offer useful insights for systems that take advantage of the spatial properties of online social services.