Carley, K.M., Frantz, T., & Diesner, J. (2006). Social and Knowledge Networks from Large Scale Databases. 56th Annual Conference of the International Communication Association (ICA). Dresden, Germany, June 19-23, 2006.
Increasingly sources data is available in electronic text form such as email, blogs, news-articles, and web page. For scientific usage, this data has to be converted to a form that can be statistically analyzed. This can be an arduous manual procedure. We present here a semi-automated approach that reduces coding time and enables the extraction from texts of a) ontologically classified networks, b) node attributes, and c) meta-data. We show that this approach makes it possible to combine network analysis and standard statistical analysis in reasoning about the material in the text and to reason both about content and the environment that produced the text. We illustrate this approach using data from two corpi – Enron email and data on political elite. Two software tools are used – AutoMap and ORA.