International discussions of scientific literacy (SL) are extensive and numerous sizeable documents on SL exist.
Thus, comparing different conceptions of SL is methodologically challenging. We developed an analytical tool
which couples the theory of complex networks with text analysis in order to obtain clear visual images of what
is meant by SL expressed in written text. The raw text was first parsed into one statement sentences. Then, a
linguistic type network was created with nodes being the words used in SL texts, and a link between two words
established if they were adjacent to each other in the one statement sentences. Using the program Pajek, we
drew a map of the text showing the number of times a concept appeared in the one statement sentences, and
the strength of links between words. Different SL texts was analysed in this way. The network description allowed
for different calculations on the network data. For example a minimal description length approach partitioned
the network in to groups of words, which was then seen to represent different visions appearing in the
discussion of SL. In short, the networks allow for quantitative analyses as well as a quick visual overview of SL
documents.