We increasingly use digital media and computational devices in our daily activities, and leave behind a sizable amount of digital traces while doing so. The proliferation of mobile devices, and the incorporation of various sensing technologies in these devices, will further add to this growing trail of data. The possibility to mine and analyze these data, and the scale at which this can be done on contemporary computer systems, affords a novel, data-driven approach in the investigation of various aspects of human behavior.

SocioPatterns is an interdisciplinary research collaboration that adopts this data-driven methodology with the aim of uncovering fundamental patterns in social dynamics and coordinated human activity.

To achieve its scientific goals, the SocioPatterns collaboration also contributes to the development of new technologies for collecting relevant data. In particular, the collaboration supports the development of the SocioPatterns sensing platform, which uses wireless wearable sensors to gather longitudinal data on human mobility and  face-to-face proximity in real-world environments.  The SocioPatterns team also works on developing tools and techniques to represent, analyze and visualize the collected data.


Composite image. Left: One of the sixty-nine daily diagrams of contact activity. Right: Thumbnail of the poster with the complete visualization and accompanying text.

Left: One of the sixty-nine daily diagrams of contact activity. Right: Thumbnail of the poster with the complete visualization and accompanying text.

We have created a visualization of sixty-nine days of face-to-face contact activity among more that 30,000 persons based on data collected during the INFECTIOUS: STAY AWAY exhibition in the Science Gallery in Dublin, Ireland. This visualization is published in our gallery as a poster that can be freely downloaded.



SocioPatterns is a collaboration between researchers and developers from the following institutions and companies:


A new high-resolution social network dataset for a primary school

We have just published a new paper in BMC Infectious Diseases where we compare different strategies for epidemic mitigation in a primary school and investigate the performance of targeted class-closure interventions.

In the Supplementary Information of the paper, we release a dataset on the face-to-face interactions in a primary school, measured by using wearable proximity sensors. The dataset covers over 200 persons (students and teachers) for about 2 days, and provides not only a complex temporal network, but also the ground truth for communities, i.e., a school class attribute for all nodes in the network. Enjoy!

Sensors on cats !

We have launched a pilot study in collaboration with Laura Ozella and her team at the University of Torino, Italy.  We aim at instrumenting colonies of feral cats in the city of Torino with new proximity sensors programmed by the ISI Data Science Lab to operate in a fully distributed fashion. We will measure the social structure of feral cat colonies in urban settings, and put these data in relation to clinical and microbiological data on cats’ health and transmissible conditions. This pilot study is part of a broader study on animal health and environmental risk factors led by Laura Ozella.



The SocioPatterns hardware goes open !

We are thrilled to announce that the long time hardware partners of the SocioPatterns collaboration, Brita Meriac and Milosch Meriac of Bitmanufaktur and OpenBeacon, have open sourced the design of their latest BLE beacons. The new beacons already support the recently announced Physical Web protocol by Google. We look forward to a surging wave of open sociometrics.



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