Digital Humanities 2016. Conference Abstracts (Jagiellonian University & Pedagogical University, Kraków, 11–16 July 2016)
The annual “Digital Humanities” conference, first held in 1989, gives a clear proof that the field of DH is, first and foremost, very well established, even if more and more subfields emerge almost every year. Secondly, the conference confirms the fact that the discipline is constantly growing. This year is no exception. Even more: the 27th joint conference of EADH (ALLC) and ACH, and the 8th conference under the auspices of ADHO, is by far the biggest event in the field, with its almost 450 accepted submissions in different categories: panels, long papers, short papers, posters, and pre-conference workshops. The number of registered participants exceeded 850 at the time of writing these words.
The conference takes place in Kraków; this is only the second time (after Debrecen 1998) that it comes to Central/Eastern Europe. The region’s rich past and its recent rapid growth has inspired the conference theme, “Digital Identities: the Past and the Future”. This theme aims at stressing the very strong connections between DH and its roots in the medieval idea of a university with a prominent role of the Liberal Arts. We strongly believe that the unique relation between the origins of the humanities’ scholarship and the opportunities provided by computer algorithms and the enormous amount of resources (text collections, linguistic corpora, databases, virtual libraries) can lead to a new scientific revolution.
The paper presents a quantitative research of characters' direct speech patterns in Leo Tolstoy's War and Peace. Tolstoy was known to put a lot of emphasis on the language in which his characters express themselves, and conscious modification of their speech is acknowledged as part of the author's literary technique. In an attempt to measure the scope and intensity of such modification, we extracted speech activity instances from the text of War and Peace, associated them with speakers and identified some distinctive features. We then used these features to train a classifier to recognize the speaker according to the speech. Our hypothesis was that if Tolstoy’s characters actually possessed any unique speech characteristics, the classifier would be able to predict the speaker with some tolerable accuracy.
The paper is devoted to the creation of information system "The First World War in Perm Provincial Periodicals" (http://permnewspapers.ru/). The system is based on ten newspapers’ collections published in Perm province (Russia) during the First World War. Publications cover periods of Imperial Russia (1914 – Feb. 1917), the 1917 Revolution and the Civil War and represent different ideological political movements. The information system can be used as a source for humanitarian studies in political, economic and social history, the history of printing and journalism, literature, linguistics, philology, cultural studies, political science, etc. The resource provides free access for scholars to images and full-texts of more than 2500 issues as well as different search tools.
Decades ago, alongside more traditional structuralist paradigms that were largely based on linguistic theorems (Lotman 1972, Titzmann 1977), literary studies began to undertake structural analyses based on empirical sociology, in particular the social network analysis. Structure was no longer solely defined by semantic relations (such as opposition or equivalence), but by social interactions, too (Marcus 1973; Stiller, Nettle and Dunbar 2003; de Nooy 2005; Stiller and Hudson 2005; Elson, Dames and McKeown 2010; Agarwal et al., 2012). In the context of the Digital Humanities, this kind of approaches has gained a new dynamic in shape of a dedicated literary network analysis (Moretti 2011; Rydberg-Cox 2011; Park, Kim and Cho 2013; Trilcke 2013). This method is based on the analysis of bigger literary corpora (i.e., quantitative data) and promises insights into the history of literature as well as generic characteristics of literary texts. In our project, "dlina. Digital LIterary Network Analysis", we already developed a workflow for the extraction, analysis and visualisation of network data from dramatic texts built on basic TEI markup (Fischer, Kampkaspar, Göbel, Trilcke, 2015). This paper will present results of our analysis of the network data gathered so far and discuss them in the light of current theories in the field of social network analysis.