The purpose of this paper is to demonstrate novel techniques for exploring relationship data extracted from social media sites for actionable insights by educators, researchers, and administrators.
The paper demonstrates how non‐programmers can use NodeXL, an open source social network analysis tool built into Excel 2007/2010, to collect, analyze, and visualize network data from social media sites like Twitter and YouTube.
Researchers and education professionals can use NodeXL to explore (a) social networks to identify important individuals and subgroups, as well as (b) content networks to map the underlying structure of a domain and find important content. Illustrative examples are provided using NodeXL to examine followers of a Twitter user focused on open education, as well as a content network of YouTube videos about surgery.
Tools like NodeXL are making network analysis accessible to non‐technical researchers in a variety of fields spanning the sciences, social sciences, and the humanities. Despite their value, network analysis techniques are only as good as the data that underlie them, requiring careful assessment of possible selection biases and triangulation of findings.
Educational institutions and educators can benefit from more systematically analyzing their social media initiatives from a network perspective.
This paper describes some of the techniques and tools needed to make sense of the social relationships that underlie social media sites. As relational data are increasingly made public, such techniques will enable more systematic analysis by researchers studying social phenomena and practitioners implementing social media initiatives.
