Using Data From Social Networks to Understand and Improve Systems
MIT News (04/07/16) Stefanie Koperniak
(reference from ACM Technews)
The Institute for Data, Systems, and Society at the Massachusetts Institute of Technology (MIT) is pursuing research merging social science with data processing and analysis. Researchers are examining interactions and dynamics over large networks of interconnected individuals with the aim of understanding how ideas evolve over networks, quantifying the influence of individuals in the networks, and making better predictions. At the heart of efforts to unravel some of the complexities and implications of social networks is “connection science,” which is an attempt to create a link between data, real-world situations, and theory. “Out of this, comes the notion of the ‘living lab;’ rather than having something happen and we record data and only then try to fit theories to it, we’re looking at something that is ongoing, living,” explains Alex Pentland, director of MIT’s Human Dynamics Laboratory. “We can interact with it to understand it better.” One initiative, involving the design of mobile phone software, enabled Pentland’s team to identify communication patterns that indicate effective collaboration, providing insight into the chemistry of high-performing groups.