Agenda Divergence in a Developing Conflict: A Quantitative Evidence from a Ukrainian and a Russian TV Newsfeeds
In this paper, we empirically test the dependence of the Russian stock market on the world stock market, world oil prices and Russian political and economic news during the period 2001–2010. We find that oil prices are not significant after 2006, and the Japan stock index is significant over the whole period, since it is the nearest market index in terms of closing time to the Russian stock index. We find that political news like the Yukos arrests or news on the Georgian war have a short-term impact, since there are many other shocks. These factors confirm the structural instability of the Russian financial market.
Modeling the processes in a healthcare system plays a large role in understanding its activities and serves as the basis for increasing the efficiency of medical institutions. The tasks of analyzing and modeling large amounts of urban healthcare data using machine learning methods are of particular importance and relevance for the development of industry solutions in the framework of digitalization of the economy, where data is the key factor in production. The problem of automatic analysis and determination of clinical pathways groups of patients based on clustering methods is considered in this research. Existing projects in this area reflect a great interest on the part of the scientific community in such studies; however, there is a need to develop a number of methodological approaches for their further practical application in urban outpatient institutions, taking into account the specifics of the organization being analyzed. The aim of the study is to improve the quality of management and segmentation of patient input flow in urban medical institutions based on cluster analysis methods for the further development of recommendation services. One approach to achieving this goal is the development and implementation of clinical pathways, or patient trajectories. In general, the clinical pathway of a patient might be interpreted as the trajectory when receiving medical services in respective institutions. The approach of developing groups of patient routes by the hierarchical agglomerative algorithm with the Ward method and Additive Regularization of Topic Models (ARTM) is presented in this article. A computational experiment based on public data on the routes of patients with a diagnosis of sepsis is described. One feature of the proposed approach is not just the automation of the determination of similar groups of patient trajectories, but also the consideration of clinical pathways patterns to form recommendations for organizing the resource allocation of a medical institution. The proposed approach to segmenting the input heterogeneous flow of patients in urban medical institutions on the basis of clustering consists of the following steps: 1) preparing the data of the medical institution in the format of an event log; 2) encoding patient routes; 3) determination of the upper limit of the clinical pathway length; 4) hierarchical agglomerative clustering; 5) additive regularization of topic models (ARTM); 6) identifying popular patient route patterns. The resulting clusters of routes serve as the foundation for the further development of a simulation model of a medical institution and provide recommendations to patients. In addition, these groups may underlie the development of the robotic process automation system (RPA), which simulates human actions and allows you to automate the interpretation of data to manage the resources of the institution.
The Ukraine Conflict. Security, identity and politics in the Wider Europe
This study explores relationship between the Internet and the Russian national election of 2011-2012. In contrast to other studies, we focus on the blogosphere as a political factor. Our conclusions are based on a study of the LiveJournal blogging platform represented by a sample of political posts from the top 2000 bloggers for 13 week-long periods. Sampling from the population of about 180,000 posts was performed automatically with a topic modelling algorithm, while the analysis of the resulting 3690 texts was carried out manually by five coders. We found that the most influential Russian blogs perform the role of a media “stronghold” of the political opposition. Moreover, we established a relationship between the weekly pre-election ratings of the opposition parties and presidential candidates and the indicators of political activity in the blogosphere. Our results cautiously suggest that political activity on the Internet is not simply an online projection of offline political activity: it can itself provoke activity in offline political life.
According to the Russian classic, there are two Russian ‘perennial questions’: Who is guilty? And what should be done? While the answer to the first question is clear to the Kremlin (of course, it’s the West - the U.S. and EU – who should be blamed for the Ukrainian crisis), the second question is still open to argument. This paper argues that the Ukrainian crisis will inevitably entail an essential revision of the Russian foreign policy’s conceptual/doctrinal basis. It also will result in changing Moscow’s regional priorities. Particularly, Russia will pay more attention to its relations with the ‘near abroad’ trying to repair its poor/negative image, prevent its authority from further weakening in the post-Ukrainian era and shift political alliances in the post-Soviet territory to its benefit. In parallel, Moscow will try to redesign the current system of Russia-led institutions in the post-Soviet space (CIS, Collective Security Treaty Organization, etc.) which proved to be inefficient during the Ukrainian crisis. The emphasis will be made on the economic aspects of integration, including the Customs Union and its further transformation to the Eurasian Union. Russia’s relations with the West and its major institutions (EU and NATO) will be redefined in a more realistic and pragmatic way with the aim to make the country less dependent on the oil and gas exports to the West and Western technologies and investment imports. At the same time, the Kremlin will make emphasis on the further development of its ‘strategic partnership’ with China and cooperation with and within non-Western institutions, such as BRICS, RIC, Shanghai Cooperation Organization, ASEAN, African Union, Islamic Conference Organization, etc.
This book constitutes revised selected papers of the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held in Moscow, Russia, in october 2020. Due to the COVID-19 pandemic the conference was held online.
The 14 full papers, 9 short papers and 4 poster papers were carefully reviewed and selected from 108 qualified submissions. The papers are organized in topical sections on natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; process mining; posters.
The paper reveals the topic structure of ethnic discussions in the Russian-speaking social media and explores how these topics are related to the post-Soviet ethnic groups. Analyzed more than 2.6 million texts from Russian-speak- ing social media published for two-year period from 2014 to 2015 and contained at least one of the post-Soviet ethnonyms, we conclude that ethnic discussions in these media are full of socially significant and potentially problematic topics (15 topics out of 97 can be regarded as problematic comparing to the 4 out of 150 topics on random sample from VK.com). The most salient topics are the topics about Ukraine-Russia relations over the recent conflict between two countries. We also found the racial bias in criminal topic towards peoples of the North Caucasus which are often mentioned in the context of crimes and terrorism.
The results of cross-cultural research of implicit theories of innovativeness among students and teachers, representatives of three ethnocultural groups: Russians, the people of the North Caucasus (Chechens and Ingushs) and Tuvinians (N=804) are presented. Intergroup differences in implicit theories of innovativeness are revealed: the ‘individual’ theories of innovativeness prevail among Russians and among the students, the ‘social’ theories of innovativeness are more expressed among respondents from the North Caucasus, Tuva and among the teachers. Using the structural equations modeling the universal model of values impact on implicit theories of innovativeness and attitudes towards innovations is constructed. Values of the Openness to changes and individual theories of innovativeness promote the positive relation to innovations. Results of research have shown that implicit theories of innovativeness differ in different cultures, and values make different impact on the attitudes towards innovations and innovative experience in different cultures.