Monday, June 28, 2010

Call for Papers: Computational Approaches to Medieval Literature
Kalamazoo 2011

The development and dissemination of electronic editions has opened up new possibilities for the computational and statistical analysis of medieval texts and corpora.  Comprehensive collections like the Dictionary of Old English Corpus (for Anglo-Saxon texts) and digital editions of individual works not only serve to disseminate widely and inexpensively various medieval texts, but also provide machine-readable data that can be analyzed using mathematical methods that previously could not easily be applied to medieval texts.  Scholars have in recent years used hierarchical agglomerative clustering methods, principle component analysis and other advanced statistical techniques to investigate authorship, influence and the structure of medieval texts.  Other methods, such as those pioneered by John Burrows, have been applied more to texts from later periods, but these approaches may also have value for the study of medieval literature in various languages. 

In this session we seek to gather together papers on computational approaches to medieval texts so that workers in this new and rapidly developing field can share results and methods.  We hope thus to disseminate ideas and methods across research groups and inform the wider scholarly community of the ways in which computational and statistical methods can augment existing work.  We also welcome papers that critique computer-aided and statistical methodologies or that modify standard approaches with more traditional methods.  Our goal is to see where matters currently stand and encourage other scholars to adopt, modify, engage with and critique the methods themselves and the methodological approach as a whole. 

Specific topics may include the types of pre-analysis processing done to texts, the problems of using editions that combine readings from multiple manuscripts, the value of and problems with lemmatization of words, and the possibilities for using computational and statistical methods across as well as within languages.

Send abstracts to