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14 June 2017

New Publication by HSE Lecturer Yury Kabanov Explores the Politics of Open Data in Russia

The article “Politics of Open Data in Russia: Regional and Municipal Perspectives”,  co-authored by our colleague from the Department of Political Science Yury Kabanov, was published in the « E-Democracy for Smart Cities» chapter of the Springer Journal this May.

1 June 2017

New Issue of HERB Focuses on International Students

In recent discussion on internationalisation, the role of international students as main drivers has been rightly reconsidered. The 12th issue of Higher Education and Beyond addresses the importance of international students for higher educational institutions and the change they bring.

29 May 2017

IOE Study Featured in International Academic Journal

A recent study by IOE research fellow Zumrad Kataeva has been published in International Higher Education, a quarterly journal by the Boston College Center for International Higher Education.

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
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
Supervised Learning for Link Prediction Using Similarity Indices
Korolev S., Zhukov L. E. In bk.: "Информационные технологии и системы 2015" 39-я междисциплинарная школа-конференция 7 – 11 сентября, Олимпийская деревня, Сочи, Россия. St. Petersburg: Институт проблем передачи информации им. А.А. Харкевича РАН, 2015. P. 1-8.

The problem of link prediction gathered a lot of attention in the last few years, arising in di erent applications ranging from recommendation systems to social networks. In this paper, we will describe the most popular similarity indices, compare their performance in their ability to show links with the highest probability of being removed from initial network and describe the approach that allows to use them to predict missing links using supervised machine learning. We will show the accuracy of prediction of this method on examples of real networks.

Added: Mar 5, 2017