Social Network Analysis with Digital Behavioral Data

Abstract

Our uses of digital technologies like social media platforms or email leave massive amounts of behavioral traces that are most interesting for social research. Other digital technologies like cell phones allow harnessing behavioral traces for research purposes. Such Digital Behavioral Data consists of genuinely relational records which can be thought of in terms of networks. However, this kind of data requires a shift of perspective from individuals to micro events (e.g., a post on social media) as units of observation and brings established techniques like Social Network Analysis to the center stage. We argue that, using this approach, obtaining individual attributes and attitudes as well as uncovering the micro-macro dynamics of behavior by mining patterns are potentially fruitful applications. We discuss methodological challenges and conclude that social theory is a constitutive pillar for the consolidation of Computational Social Science.