Search

The paper applied SOCMINT (Social Media Intelligence) techniques to discover cybersecurity-related information from the contemporary Russia-Ukraine conflict. Using open-source tools and APIs, datasets created were assessed through topic modeling, thematic analysis (word cloud), Logit function, and neural network classification. The topic modeling and word cloud yielded trifling insights, but Logit and neural network classifier, MLP, suggested statistically significant features that were important to the outcome of the tweets with reasonable accuracy of 91%. Through the use of synthetic data (GaussianCopula) and feature selection(stepAIC), the model was extended to improve accuracy, which resulted in 96% accuracy, though, such competent performance requires further investigation. While deciphering the right intelligence is a challenge due to the unruly nature of social media, this nascent technique can be helpful with the proper framework and approach. [ABSTRACT FROM AUTHOR]

This empirical analysis is based on the latent variable framework to identify key determinants of protests in Russia during 2011-2012. We derive logistic regressions from the revolution constraints based on economic (the political Kuznets Curve) and socio-psychological (grievance) theories of protest. Our findings suggest a positive linear relationship between income and income inequality, contradicting the Kuznets curve. Our estimations show that inequality, share of the poor, the relation of the governor's family income to the average family income, distance to Moscow and accumulated human capital increase the risk of protest, whereas transfers and subsidies decrease these risks. [ABSTRACT FROM AUTHOR]

In this article, we use logit models to examine the role of the major characteristics of a political party's organization, (1) legitimation, (2) penetration/diffusion, (3) charisma, (4) ideology and (5) centralization/decentralization, in the institutionalization of parties in both pre-Soviet and post-Soviet Russian national parliamentary elections. The article begins by situating this research in the context of the theoretical and empirical literature on party origins, organizational development and institutionalization, in general, and party formation theories in post-communist countries, specifically. The impact of organizational features on electoral success or failure is analysed for 24 parties. The models correctly predicted both the successful and failed parties in the 2007 Russian Duma election and offer reasons for the apparent floating party system in Russia. [ABSTRACT FROM PUBLISHER]

Owing to a combination of domestic, regional and international factors, Russian banks have been strongly influenced by the worldwide financial crisis which started in the second half of 2008. In this paper, we estimate an early warning model for the Russian banking crisis. In a first step, we identify 47 Russian banks which failed after September 2008. Using the Bankscope dataset, we then show that balance sheet indicators were informative as early as in 2006 and 2007 about possible failures of these banks. Especially equity, net interest revenues, return on average equity, net loans, and loan loss reserves are identified as the early indicators with high predictive power. [ABSTRACT FROM AUTHOR]