Indiana University Network Science Institute

Abstract: Folklore collections are generally indexed according to the dictum, "one story, one classifier." This approach to collection indexing was generally serviceable as long as the research questions aligned with indexing practices, and as long as the collections were relatively small. As research questions changed and collections became much larger--including stories from thousands or tens of thousands of storytellers, and constituting tens of thousands of pages or hours of recording--these simple finding-aids were revealed to be inadequate for addressing even the simplest needs of researchers. Using a 19th century collection of Danish folklore, we explore the use of network analysis tools for search and discovery. We show how a tuned Markov Clustering (MCL) algorythm can be (a) used to discover stories needed to address research questions not considered by the initial indexing scheme and (b) find previously unrecognized affinities among stories that can lead to new research questions. A second part of the presentation focuses on how to visualize geographic relations between individuals and their story repertoires. The audience is reminded not to present clothing to the house elf accompanying the lecturer.

Bio: Timothy R. Tangherlini teaches folklore, literature and cultural studies at the University of California, where he is a professor in Scandinavian Section, and the Department of Asian Languages and Cultures. He is the author of Interpreting Legend: Danish Storytellers and their Repertoires (1994), Talking Trauma. Paramedics and Their Stories (1998), and the co-editor of Nationalism and the Construction of Korean Identity (1999), and Sitings. Critical Approaches to Korean Geography (2008). He has also produced or co-produced two documentary films, Talking Trauma: Storytelling Among Paramedics (1994) and Our Nation. A Korean Punk Rock Community (2002). His current work focuses on computation and the humanities. In particular, he has focused on using GIS to discover patterns in folklore collections, and network analysis techniques to address problems of classification. Links to this work can be found at http://tango.bol.ucla.edu/#online. He directed the NEH's "Networks and Network Analysis for the Humanities" Summer Institute for Advanced Topics in Digital Humanities at NSF's Institute for Pure and Applied Mathematics at UCLA in summer 2010. His research has been supported by grants from the National Science Foundation, the National Endowment for the Humanities, the Fulbright Foundation, the Nordic Council of Ministers, the John Simon Guggenheim Memorial Foundation, the American Council of Learned Societies, The Henry Luce Foundation, the American Scandinavian Foundation, and Google.