Also, given data from different time periods, a series of maps may be produced to trace the conceptual changes in the field over a long period of time. Our goal in applying this technique to humanities computing literature is two-fold. First, we are naturally seeking to learn more about the method's effectiveness and limitation by broadening our work to examine more discipline areas. Second, we believe this work can say something useful about the discipline of humanities computing itself. Clearly scholars in this field might be able to agree upon broad conceptual areas of research that make up humanities computing, but it is intriguing to see if these areas can be identified empirically from the research literature itself.
Practical results are also possible.
These results are encouraging in that they identify what the authors recognize as important topics that were addressed at these conferences. This last result is not surprising, and in fact shows that the method is able to recognize verbal characteristics of the genre in addition to the texts' subject matter based on word associations. We will give some details of these results at the end of this proposal. Our plan is to expand this study before the conference by looking at papers published in the journal Computers and the Humanities. Used Co-word analysis deals directly with sets of terms shared by documents.