There are dozens of social media tools that offer the ability to graph the connections between accounts, hashtags, shared URLs and other forms of content. These are very powerful tools that can help the analyst or the investigator quickly assess who is important in a network and where individuals or organizations may be located, and it is all available in the public domain. For example, this page provides 10 Awesome Twitter Analytics and Visualization Tools .
Computer scientists use language that analysts and investigators don’t necessarily use. For the person just beginning to explore the power of graph analysis we suggest work by Charles Perez, Associate Professor of Computer Science at the Paris School of Business.
First get a copy of the book Automating Open Source Intelligence, Algorithms for OSINT edited by Robert Layton and Paul A. Watters. It is a collection of white papers on automating Open Source Intelligence gathering. Charles Perez and Rony Germon wrote a white paper entitled “Graph Creation and Analysis for Linking Actors: Application to Social Data” which is included at at Chapter 7 of the book. It is an excellent overview of Graph theory and terminology such as Nodes, Edges, Directed and Undirected interactions.
A second paper, which is freely available online entitled Analysing Human Migrations Patterns Using Digital Social Network Analysis was also written by Perez and it also provides an overview of basic graphing terminology. It then provides a case study of how it might be combined with geo-spatial data in social networks (in this case Twitter).
Being conversant in the basic concepts of graphing theory will allow investigators and analysts to interrogate data more effectively (or ask colleagues to interrogate it more effectively). It will also help them understand how things like Facebook’s graph works.
For more information on these resources and others, please contact us.