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.
FEATURED: INFECTIOUS SOCIOPATTERNS POSTER
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:
Ciro Cattuto is presenting a review of our results in the workshop Temporal and Dynamic Networks: From Data to Models taking place on June 3-4, 2013 in Copenhagen, Denmark as a satellite of NetSci2013. Moreover, Laetitia Gauvin presented new results on “The activity-community structure of time-varying networks: A non-negative tensor factorization approach” in the workshop on Dynamic Information and Communication Networks 2013.
Alain Barrat has presented the results of our recent paper “An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices” at the “Digital Epidemiology” workshop that took place at ISI Foundation, Turin, on May 30-31, 2013.