How many makes a crowd? On the evolution of learning as a factor of community coverage

Yaniv Altshuler, Michael Fire, Nadav Aharony, Yuval Elovici, Alex Pentl,

Social Computing, Behavioral-Cultural Modeling and Prediction: 5th …, 2012

As truly ubiquitous wearable computers, mobile phones are quickly becoming the primary source for social, behavioral and environmental sensing and data collection. Today’s smartphones are equipped with increasingly more sensors and accessible data types that enable the collection of literally dozens of signals related to the phone, its user, and its environment. A great deal of research effort in academia and industry is put into mining this raw data for higher level sense-making, such as understanding user context, inferring social networks, learning individual features, and so on. In many cases, this analysis work is the result of exploratory forays and trial-and-error. In this work we investigate the properties of learning and inferences of real world data collected via mobile phones for different sizes of analyzed networks. In particular, we examine how the ability to predict individual features and social links is …