Connecting Productivity with Social Capital via Daily Mobile Phone Logs

Abstract

Human behavior and their social interactions can be quantified and modeled with the use of smart phones and any wearable badges which senses and captures real-life interactions. In traditional social sciences, such information was gathered by conducting surveys. However in digital era, smart phones are regarded as a popular tool which automatically senses much human information to quantify our lives. Reality mining gives a clear picture of a human being and its social relations. Social Network Analysis (SNA) is a powerful research tool which provides a comprehensive analysis on ego-alters communications with their individual productivity within a community. In this paper, various popular measures of social network analysis have used to study a closed community through their mobile call logs for a period of time. We experimented various social network measures both on daily basis and also over a period of time. The pattern shows that the relationships and interaction between ego-alter ties have more productive benefits. Using Pearson-correlation analysis, we observed that significant (positive) correlation exists between various network properties and their productivity. Results showed that degree (size) has the strongest positive correlation with average productivity, followed by effective size, efficiency, constraint, hierarchy, and k-core of an individual. Density and betweenness centrality have a weak, negative correlation with productivity. Hence social capital has a significant influence on human productivity.