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25 April 2018

I’m (Not) Afraid to Say: What Are the Limits of Frankness in Posts about Sexual Violence

The #imnotafraidtosay (Russian: #янебоюсьсказать) flashmob on Facebook and other online actions against sexual violence have helped victims to speak out about the problem and get psychological support from the web. At the same time, full frankness is hardly possible in such projects. It is directly related to anonymity. According to HSE researchers, the most painful experiences are still muted in groups where the discussants use their real names.

24 April 2018

‘The Biggest Priority in Education Is World Class Professional Development Programmes’

The report entitled ‘Twelve Solutions for New Education’, prepared by the Higher School of Economics and the Centre for Strategic Development, was presented at the XIX April International Academic Conference. Professors Martin Carnoy and Tomasso Agasisti, international experts on education and conference guests, have shared their views on the issues and initiatives highlighted in the report.

23 April 2018

Instagram Micro-celebrities: What Factors Contribute to Online Endorser Credibility and Influence Consumer Behaviour?

Physical attractiveness, high-quality photos, interesting content, engagement with the audience, and subject competence are the key contributing factors to Instagram micro-celebrities' success, according to a study which examines the influence of online celebrity endorsers on consumer purchase intentions.

Book chapter

Digitale Netzwerkanalyse dramatischer Texte

Trilcke P., Fischer F., Kampkaspar D.

Das Projekt ‘Digitale Netzwerkanalyse dramatischer Texte’ steht in der Tradition strukturanalytischer Ans¨atze in der Literaturwissenschaft (allgemein Titzmann 1977), die es einerseits im Sinne eines konsequent netzwerkanalytischen Relationismus (mit Rekurs auf die Social Network Analysis, siehe u. a. Wasserman/Faust 1998), andererseits unterstutzt durch Verfahren der automatisierten ¨ Datenerhebung und -auswertung weiterentwickelt, um sie auf gr¨oßere Textkorpora anzuwenden und so umfassende relationale Daten uber Prozesse des literaturgeschichtlichen Strukturwandels ¨ gewinnen zu k¨onnen.

Language: German
 Text on another site
Keywords: Network Analysis

In book

DHd2015. Von Daten zu Erkenntnissen 23. bis 27. Februar 2015, Graz. Book of Abstracts
Austrian Centre for Digital Humanities, 2015.
Similar publications
Easy Linavis (Simple Network Visualisation for Literary Texts)
Fischer F., Milling C., Shlosman E. et al. In bk.: Digital Humanities Russia 2017. Vol. 1. Krasnoyarsk: Siberian Federal University, 2017.

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The purpose of Easy Linavis is not to compete with more sophisticated methods of extracting networks from literary texts, but is intended for didactic use in teaching, to take first steps from theory to practice.

Added: Dec 7, 2017
Сетевой анализ в контексте различных научных и прикладных дисциплин Репортаж с XVIII Апрельской международной научной конференции по проблемам развития экономики и общества, 11–14 апреля 2017 г., Москва, Россия
Моисеев С. П., Карпов И. А., Мифтахутдинова К. И. и др. Экономическая социология. 2017. Т. 18. № 3. С. 152-159.

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). 

 

Added: Sep 16, 2017
Assessment of Exporting Economies Influence on the Global Food Network
Aleskerov F. T., Сергеева З. В., Shvydun S. V. In bk.: Optimization Methods and Applications, In Honor of Ivan V. Sergienko's 80th Birthday, Springer Optimization and Its Applications. Vol. 130. Springer International Publishing, 2017. P. 1-10.

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.

Added: Mar 3, 2018
Centrality Measures And Clustering Analysis in a Retail Food Network
Aleskerov F. T., Meshcheryakova N. G., Сергеева З. В. et al. In bk.: 2017 IEEE 11th International Conference on Application of Information and Communication Technologies. Vol. 1. M.: Institute of Electrical and Electoronics Engineers, 2017. P. 48-52.

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.

Added: Sep 24, 2017
Network analysis of international migration
Aleskerov F. T., Meshcheryakova N. G., Rezyapova A. et al. Математические методы анализа решений в экономике, бизнесе и политике. WP7. Издательский дом ВШЭ, 2016. No. WP7/2016/06.
The paper analyses international migration flows from the network perspective by the evaluation of centrality indices. In order to find the most influential countries in the international migration network classical centrality indices and new centrality indices are evaluated. New centrality indices consider short (SRIC) and long-range (LRIC) indirect interactions and the node attribute – population of the destination country. The model is applied to the annual data on international migration flows from 1970 to 2013 provided by United Nations Organization. The analysis is made for one year of each decade and indices’ dynamics is described. It is shown that countries with huge migration flows are outlined by both classical and SRIC, LRIC indices, and SRIC and LRIC indices point out countries with considerable outflows of migrants to countries highly involved in international migration and the most interconnected countries.
Added: Nov 2, 2016
Le drame comme réseau de relations. Une application de l’analyse automatisée pour l’histoire littéraire du théâtre
Fischer F., Dazord G., Göbel M. et al. Revue d'Historiographie du Théâtre. 2017. Vol. 4.

Of late, the network analysis of literary texts has grown into an independent research field of digital literary studies. Since analysing the network structure of unique texts promises just marginal results, the perspective should shift towards a ‘distant reading’ of hundreds or thousands of texts. In this paper, we describe how the process of formalising literary data is facilitated by machine-readable corpora comprising hundreds of dramatic texts in several languages. Taking a corpus of roughly 500 German-language dramas as an example, we demonstrate how the calculation of network metrics and visualisations can deliver new material for interpretation and offer new insights into the evolution of drama.

Added: Dec 27, 2017