Introducing RusDraCor – A TEI-Encoded Russian Drama Corpus for the Digital Literary Studies
We describe the creation of a corpus of Russian-language drama, comprising hundreds of texts from the middle of the 18th century to the first third of the 20th century. Texts are encoded in the XML-based markup standard TEI, the focus is on extra-linguistic, structural annotations, although additional annotation layers can be added easily.
A “Network Analysis” section was arranged at the XVIIIth Interna- tional Academic Conference on Economic and Social Development at the Higher School of Economics on 11–12 April 2017. For the third year, this section invited scholars from sociology, political science, management, mathematics, and linguistics who use network analysis in their research projects. During the sessions, speakers discussed the development of mathematical models used in network analysis, studies of collaboration and communication networks, networks’ in- uence on individual attributes, identifcation of latent relationships and regularities, and application of network analysis for the study of concept networks.
The speakers in this section were E. V. Artyukhova (HSE), G. V. Gra- doselskaya (HSE), M. Е. Erofeeva (HSE), D. G. Zaitsev (HSE), S. A. Isaev (Adidas), V. A. Kalyagin (HSE), I. A. Karpov (HSE), A. P. Koldanov (HSE), I. I. Kuznetsov (HSE), S. V. Makrushin (Fi- nancial University), V. D. Matveenko (HSE), A. A. Milekhina (HSE), S. P. Moiseev (HSE), Y. V. Priestley (HSE), A. V. Semenov (HSE), I. B. Smirnov (HSE), D. A. Kharkina (HSE, St. Petersburg), C. F. Fey (Aalto University School of Business), and F. López-Iturriaga (Uni- versity of Valladolid).
Conference abstracts for DHd2017, Bern. (http://www.dhd2017.ch/)
Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks.
This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.
Using network approach, we propose a new method of identifying key food exporters based on the long-range (LRIC) and short-range interaction indices (SRIC). These indices allow to detect several groups of economies with direct as well as indirect influence on the routes of different levels in the food network.
Trading processes is a vital part of human life and any unstable situation results in the change of living conditions of individuals. We study the power of each country in terms of produce trade. Trade relations between countries are represented as a network, where vertices are territories and edges are export flows. As flows of products between participants are heterogeneous we consider various groups of substitute goods (cereals, fish, vegetables). We detect key participants affecting food retail with the use of classical centrality measures. We also perform clustering procedure in order to find communities in networks.
In 19th century Germany, the number of publications in the history of philosophy increased dramatically. According to Schneider’s (1999) calculations, from 1810 through 1899, 148 original textbooks by 114 authors were published in German. The aim of this article is to analyse how the documented in these publications canonic vision of 19th century German philosophy evolved. An analysis of 66 treatises published from 1802 through 1918 allows dividing 19th century philosophers into groups based on the frequency of their names across the tables of contents, describing the changes in the leading group composition and in the share of attention received by a given philosopher over time (the patterns of attention for Kant, Fichte, Hegel, Schelling, Herbart, Schleiermacher, Schopenhauer, Jacobi and Fries are discussed in detail). The paper presents thus a formal analysis of how historical reputations of philosophers were made, how they stabilised, or faded. The authors claim that the current understanding of the history of 19th century philosophy differs significantly from the one recorded in the German textbooks of the era (e.g. Herbart’s key position within the 19th century philosophical Canon; Schopenhauer’s recognition by university philosophers during his own lifetime).