?
Educational Migration from Russia to China: Social Network Data
P. 309–311.
This paper presents the results of our study of educational migration flows between Russian Federation and China. Using data from the most popular among Russian-speakers Social Networking Site VK, we explore "digital footprints" of migration, analyzing the factors influencing the size of migration flows from different Russian cities to China. We take into account different groups of parameters, in particular, geographic proximity of a city to China and to Russian educational centers, institutional presence of China, and Chinese web presence in the particular city. Resulting conditional inference tree with the relative number of educational migrants from each city as the outcome has R2 = .86
Keywords: decision treesWeb Sciencesocial informaticssocial computingeducational migrationrandom forest
Publication based on the results of:
Cham: Springer Publishing Company, 2023.
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or ...
Added: February 26, 2026
Shchepeleva M., Финансы: теория и практика 2025 Т. 29 № 4 С. 146–162
This research is devoted to the analysis of financial crises. We examine different classifications of crises, methods of forecasting, approaches to building systems of early warning indicators. To better understand the potential for predicting financial crises, we conduct our own empirical research, comparing Logit model and random forest to predict currency crises in developing countries. ...
Added: February 12, 2026
Soldatova A., Финансы, деньги, инвестиции 2023 № 4 С. 9–15
The price of gold is the most important economic indicator. Expectations of rising inflation and higher key rates from central banks are driving investor interest in gold around the world. Given the increasing number of factors influencing the dynamics of the gold rate in the world, forecasting gold prices requires new methods and modern technological ...
Added: July 8, 2025
Shchepeleva M., Procedia Computer Science 2024 Vol. 242 P. 51–56
We test the predictive performance of different ensemble methods for forecasting systemic risk in Russia for the period 2008-2024. In contrast to the existing research on machine learning ensemble techniques, we find that conventional random forest works better for the Russian data. Based on this model, we additionally conduct variable importance analysis. We identify that ...
Added: June 17, 2025
Forecasting Stadium Attendance Using Machine Learning Models: A Case of the National Football League
Пан Ю., Wang F., Studia Sportiva 2024 Vol. 18 No. 2 P. 147–164
Added: May 16, 2025
Saryglar S., Gabdrakhmanov N., В кн.: Развитие экспертных институтов в XXI веке: теория и практика : Сборник научных трудов Третьей международной научно-практической конференции.: Иркутск: Иркутский государственный университет, 2024.
В статье обосновывается, что исследование образовательной миграции, в основном, построено на анализе статистики межрегиональной миграции и состояния социально-экономического положения регионов. Отмечается, что данные официальной статистики позволяют лишь констатировать факт миграции, поэтому исследование качественных характеристик, причин, факторов образовательной миграции требует использования не только традиционных статистических методов, но также применения социологических методов, а также новых методов и ...
Added: May 12, 2025
Pshichenko D., International Journal of Humanities and Natural Sciences 2024 Vol. 8-3(95) P. 180–185
This study explores the application of artificial intelligence (AI) and machine learning (ML) models for big data analysis in project management. By leveraging specific ML algorithms such as decision trees, random forests, support vector machines, neural networks, kmeans clustering, gradient boosting, and natural language processing, project management practices are significantly enhanced. These technologies improve decision-making, ...
Added: March 10, 2025
Lisovskaya I., Гарифзянова А. Р., Мониторинг общественного мнения: Экономические и социальные перемены 2025 № 2 С. 22–44
The article raises the issue of social inclusion of non-resident student youth through different ways of engaging with the university and the city as specific environments with important resources. This article contributes to the field of post-migration research and provides insights into the processes that occur with young people after moving within the country. Social ...
Added: February 21, 2025
Afanasev V., Финансы и бизнес 2024 Vol. 20 No. 3 P. 71–88
The conventional approach to default prediction implies using financial ratios as predictors. This paper provides evidence for improvement in the quality of default prediction for auto repair firms if non-financial data is included in the models. The study uses a sample of more than 200 firms, which defaulted in 2018–2023 and 10 healthy peers samples ...
Added: October 2, 2024
Cham: Springer, 2024.
This book constitutes the refereed proceedings of the 16th International Conference on Social Computing and Social Media, SCSM 2024, held as part of the 26th HCI International Conference, HCII 2024, which took place in Washington, DC, USA, during June 29–July 4, 2024.
The total of 1271 papers and 309 posters included in the HCII 2024 proceedings ...
Added: July 16, 2024
Ignatenko V., Surkov A., Sergei Koltcov, PeerJ Computer Science 2024 Vol. 10 Article e1775
The random forest algorithm is one of the most popular and commonly used algorithms
for classification and regression tasks. It combines the output of multiple decision trees
to form a single result. Random forest algorithms demonstrate the highest accuracy on
tabular data compared to other algorithms in various applications. However, random
forests and, more precisely, decision trees, are usually ...
Added: February 16, 2024
Bukina T. V., Kashin D., Экономический журнал Высшей школы экономики 2024 Т. 28 № 1 С. 81–107
The paper reveals the forecasts for regional inflation based on the regions of the Privolzhskiy Federal District (PFD). The purpose of the study is to determine the model that most accurately predicts regional inflation. The paper compares the tools of machine learning – support vector machines, gradient boosting, and random forest – with econometric models ...
Added: February 13, 2024
Lisovskaya I., Omelchenko E. L., Гарифзянова А. Р., Вопросы образования 2024 Т. 2 № 3 С. 136–170
The needs of young people who have moved to study from other cities are often overshadowed by numerous studies of international students, traditionally considered by sociologists and practitioners to be among the most vulnerable groups. In this article, we focus on the migration paths of out-of-town students in megacities and what they face on their ...
Added: December 11, 2023
Ponomarenko A. A., Татаринцев С. А., Journal of Economic Asymmetries 2023 Vol. 27 Article e00284
We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators in addition to conventional imbalances measures. The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that ...
Added: March 28, 2023
Sakaev V., Мониторинг общественного мнения: Экономические и социальные перемены 2022 № 6(172) С. 243–264
The paper concerns the perception of interethnic relations in the face of the challenges of the COVID-19 pandemic by non-resident and foreign students — representatives of the Turkic peoples studying in Moscow universities. Empirically, the study bases on the materials of a series of in-depth interviews conducted in the fall of 2021 with 85 respondents ...
Added: January 22, 2023
Stolbov M., Shchepeleva M., Risks 2022 Vol. 10 No. 12
This paper seeks to identify the most important global drivers of credit-to-GDP gaps for 35 countries. The analysis is performed on a country-by-country basis for the sub-periods 2000Q1:2007Q2, 2007Q3:2013Q4, and 2014Q1:2021Q1 and is based on two state-of-the-art methods for variable selection in the time series framework: the one covariate at a time multiple testing (OCMT) ...
Added: January 5, 2023
Чернышёва Н. С., Чжан Ю., Социологические исследования 2022 № 11 С. 135–143
An overview of the Russian scientific discussion on internal youth migration is offered. The first part contains statistical data on the age and educational composition of internal migrants, describes the types and main causes of youth migration. The second part analyzes discussions of Russian researchers about youth migration: attitudes and intentions, sense of place for ...
Added: November 29, 2022
Muratova A., Ignatov D. I., Mitrofanova E., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 297–299.
This is the extended abstract of a case study on demographic sequences analysis by machine learning and data mining methods. ...
Added: November 1, 2022
Hajdu N., Schmidt K., Acs G. et al., Plos One 2022 Vol. 17 No. 11 Article e0276970
Voluntary isolation is one of the most effective methods for individuals to help prevent the transmission of diseases such as COVID-19. Understanding why people leave their homes when advised not to do so and identifying what contextual factors predict this non-compliant behavior is essential for policymakers and public health officials. To provide insight on these ...
Added: October 18, 2022
Samadova M., В кн.: Миграция и общество в ЕС и России: дискурсы, практики, нарративы : сборник материалов Международного научно-практического семинара 6–10 августа 2018 года.: М.: Русайнс, 2018. С. 88–94.
The object of the research is educational migrants from the SCO member countries. The subject of the research is the process of adaptation and integration of educational migrants in the host society. There was examined the whole chain of the educational migration process in this research: starting from the reasons for choosing Russia as a ...
Added: August 26, 2022
Kasprzhak A. G., Белоусов Д. В., Kobtseva A. et al., Образовательная политика 2022 № 1(89) С. 66–79
This project describes the network educational programs of specialized training for high school students. After analyzing the theoretical models and specific practices of implementing network educational programs for specialized education of high school students in Russia, the People's Republic of China and Great Britain, the authors highlight the grounds for their design. The work focuses ...
Added: July 12, 2022
Chernenkova T., Kotlov I., Belyaeva N. et al., Remote Sensing 2021 Vol. 13 No. 10 Article 1886
Forests with predominance of Norway spruce (Picea abies (L.) H. Karst.) and Scots pine (Pinus sylvestris L.) within the hemiboreal zone are considered as secondary communities formed under long-term human activity (logging, plowing, fires and silviculture). This study raises the question—how stable is current state of coniferous forests on the southern border of their natural distribution in ...
Added: March 20, 2022