A natural response to unsustainable increases in energy production and use is to seek ways that each of us can decrease our energy footprint. However, it is daunting to identify and adopt personal lifestyle modifications that result in meaningful reduction or elimination of energy consumption. Development and maintenance of social networks is an arena where we face choices that could reduce our energy impact. However, the energy costs of social network choices are currently unknown or difficult to estimate, making it challenging to offer prescriptive recommendations. This talk describes a new program of research at the University of Michigan that addresses this challenge through: assessment of the ways different technologies are used in concert to help people build and maintain social networks; measurement of the use-phase power consumption of social network technologies, including social computing; and development of approaches to model the overall use-phase power consumption of an individual’s social network across information and transportation systems. Expected contributions of this work include the first descriptive and predictive models of social network energy use and identification of individual behavioral changes with the greatest ability to reduce overall energy consumption associated with social networks.