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Discerning Depression Propensity Among Participants of Suicide and Depression-Related Groups of Vk.com
Ch. 3. P. 24–35.
In online social networks, high level features of user behavior such as character traits can be predicted with data from user profiles and their connections. Recent publications use data from online social networks to detect people with depression propensity and diagnosis. In this study, we investigate the capabilities of previously published methods and metrics applied to the Russian online social network VKontakte. We gathered user profile data from most popular communities about suicide and depression on VK.com and performed comparative analysis between them and randomly sampled users. We have used not only standard user attributes like age, gender, or number of friends but also structural properties of their egocentric networks, with results similar to the study of suicide propensity in the Japanese social network Mixi.com. Our goal is to test the approach and models in this new setting and propose enhancements to the research design and analysis. We investigate the resulting classifiers to identify profile features that can indicate depression propensity of the users in order to provide tools for early depression detection. Finally, we discuss further work that might improve our analysis and transfer the results to practical applications.
Publication based on the results of:
In book
Vol. 542: Series: Communications in Computer and Information Science. , Switzerland: Springer, 2015.
Maltseva D., Shcheglova T., Vashchenko V., Социологические исследования 2026 № 1 С. 62–74
The article continues to present the results of the analysis of collaboration networks of Russian sociologists in 2010–2021. It was conducted on the basis of data on co-authorship of scientific articles indexed in the electronic library eLibrary (75,232 scientific publications on sociology). The methodology of bibliometric network analysis implies the construction of several types of ...
Added: May 12, 2026
Neznanov A., Glushko A., Овчинников С. et al., В кн.: Интеллектуальный анализ данных в нефтегазовой отрасли.: М.: ООО «Геомодель Развитие», 2024. С. 140–143.
With the development of monitoring systems, now we have the opportunity to collect key performance indicators of devices in the process of artificial lift. Every day a huge amount of telemetry is generated by our devices, which can be used to forecast the working mode and health state of the equipment after the process of ...
Added: April 29, 2026
Neznanov A., Емельянов В., Glushko A. et al., В кн.: Интеллектуальный анализ данных в нефтегазовой отрасли.: М.: ООО «Геомодель Развитие», 2024. С. 42–45.
The complexity of data processing in corporate information systems at the oil and gas industry is constantly growing due to increasing data quantity and heterogeneity. It requires the adoption of modern methodologies and tools for data and knowledge management. Many architectural solutions have already been tested by the OSDU consortium, but in the current conditions ...
Added: April 29, 2026
Maltseva D., Kim A., Kapustina L., Социологические исследования 2025 № 12 С. 50–65
В работе представлены результаты библиометрического анализа паттернов коллаборации российских социологов в 2010–2021 гг. на основе соавторства научных работ как наиболее частой формы сотрудничества в науке. На основе данных из научной электронной библиотеки eLibrary (75 232 публикации) построены сети коллаборации нескольких типов, которые включают 37 790 уникальных авторов. В первой части статьи данные проанализированы на макро- ...
Added: January 15, 2026
Tyul’bashev S., Samodurov V., Pozanenko A. S. et al., Publications of the Astronomical Society of Australia 2025 Vol. 42 Article e059
Since August 2014, a monitoring survey at a frequency of 111 MHz has been conducted on the Large Phased Array (LPA) radio telescope of the P.N. Lebedev Physical Institute (LPI). We report the discovery of a bright pulse having a dispersion measure (DM) equal to 134.4±2 pc cm−3, a peak flux density ( Sp ) equal to 20±4 Jy, and a ...
Added: November 20, 2025
Бояров Е. Н., Абрамова С. В., Шитов Э. Н. et al., В кн.: Приморские зори - 2024: Международные научные чтения: сборник научных трудов, Владивосток, 18–20 апреля 2024 года.: Владивосток: Дальневосточный федеральный университет, 2024. С. 166–170.
В статье проведен анализ необходимости и эффективности применения современных средств, в частности искусственного интеллекта и больших данных, в процессах моделирования управления производственными и профессиональными рисками. Рассматривается, каким образом интеграция передовых технологических решений способствует повышению точности прогнозирования потенциальных рисков, а также обеспечивает оптимизацию ресурсов и процессов управления рисками в организациях. Освещаются основные этапы построения моделей управления ...
Added: September 24, 2025
Popov V., Chepovskiy A., Вопросы кибербезопасности 2025 № 4(68) С. 73–83
Цель исследования: разработка метода определения цифрового профиля Telegram-каналов в сетях информационного взаимодействия и процедуры классификации каналов на основе выделенного цифрового профиля.
Метод исследования: метод исследования включает следующие этапы: построение графа взаимодействующих объектов на основании импортированных из сети Telegram данных, определение цифровых профилей вершин на основании их атрибутивных данных и свойств графа, кластеризация вершин на основании выделенных ...
Added: September 6, 2025
Dvoinin A., Информация и образование: границы коммуникаций 2025 Т. 25 № 17 С. 125–127
The article discusses problems of applying statistical methods in pedagogical research: the lack of informative indicators, template types of analysis, fabrication of calculations, p-hacking and others. ...
Added: August 19, 2025
Loginova I., Пиекалнитс А. С., Grozovskiy F., Социология: методология, методы, математическое моделирование 2025 № 60 С. 36–88
Цель настоящей статьи заключается в демонстрации подходов по анализу связей центров компетенций с использованием системы интеллектуального анализа больших текстово-документных данных iFORA на примере картирования области «Промышленные информационноуправляющие и телекоммуникационные системы». Результаты исследования включают апробацию реализованных в системе iFORA подходов и методов к задачам, которые традиционно решаются в рамках организационного сетевого анализа. Основной результат проведенного анализа ...
Added: August 6, 2025
KUDRYAVTSEVA A., Cancers 2023
Liver metastasis is a significant factor contributing to mortality associated with colorectal cancer. Establishing the biological mechanisms of metastasis is crucial for refining diagnostics and identifying therapeutic windows for interventions. Currently, little is known of the processes that govern the development of liver metastases, the role of the tumor microenvironment, the role of epigenetics, and ...
Added: July 1, 2025
Maltseva D., Kim A., Semenova A., Operations Research Forum 2025 Vol. 6 Article 89
Due to the non-linear nature of the development of the sociological discipline in the Soviet time, and the existing inequality between central cities and regions in mod- ern Russia, the community of Russian sociologists is characterized by a low level of integration at the local level and selective representation in the international sci- entific community. ...
Added: June 26, 2025
Springer, 2024.
This book constitutes the refereed proceedings of the 12th International Conference on Analysis of Images, Social Networks and Texts, AIST 2024, held in Bishkek, Kyrgyzstan, during October 17–19, 2024.
The 16 full papers included in this book were carefully reviewed and selected from 70 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; ...
Added: May 29, 2025
Maillard J. P., Mihalchenko A., Novikov D. et al., Physical Review D - Particles, Fields, Gravitation and Cosmology 2024 Vol. 109 No. 2 Article 023523
We present a signal-foreground separation algorithm for filtering observational data to extract spectral distortions of the cosmic microwave background (CMB). Our linear method, called the least response method (LRM), is based on the idea of simultaneously minimizing the response to all possible foregrounds with poorly defined spectral shapes and random noise while maintaining a constant ...
Added: April 26, 2025
Stegnii E., Информационное общество 2025 № 6 С. 107–120
Статья посвящена методологии анализа социальных сетей или сетевого анализа (SNA – Social Network Analysis) и ее применения в сфере организационного поведения и управления человеческими ресурсами (УЧР). Приводятся данные двух этапов исследования: систематизированного библиометрического анализа зарубежной литературы; классификации наиболее релевантных источников. В результате анализа отобраны 110 наиболее релевантных источников и классифицированы по 9 тематическим областям. В статье ...
Added: April 17, 2025
Gorshkov S., Ignatov D. I., Chernysheva A., IEEE Access 2025 Vol. 13 P. 46732–46746
This paper presents a novel approach to predicting student dropout by analyzing publicly available data from VKontakte social network profiles. Unlike traditional methods that primarily rely on academic and institutional data, our method leverages publicly available content, including photos, videos, music preferences, and textual posts. Image and video content were analyzed using scene recognition models ...
Added: March 20, 2025
Pavlenko B., Вопросы теоретической экономики 2025 № 2 С. 144–163
Economic inequality in Russia is extensively researched and well-documented. However, most studies have focused on regional disparities, while inequality within individual towns in Russia remains understudied. This study examines the relationship between bonding social capital—measured through social network analysis—and inequality at the town level. Using data from the online social network “VK,” we constructed fragmentation ...
Added: March 11, 2025
Ишанхонов А. Ю., Pshichenko D., Можаровский Е. А. et al., Программные системы и вычислительные методы 2024 № 4 С. 140–150
The role of Large Language Models (LLM) in new generation integrated development environments (IDEs). Tools such as GitHub Copilot, IntelliCode and Alice Code Assistant are explored in the context of their use in programming. The authors examine how LLMs enable the automation of key development tasks, including code autocompletion, error detection, refactoring, and code generation, ...
Added: March 10, 2025
Кузнецов И. А., Бобунов А. Ю., Бушуев С. А. et al., Конкурентоспособность в глобальном мире: экономика, наука, технологии 2024 № 9 С. 56–61
he article explores modern technologies employed in content recommendation systems (CRS) using Big Data. It examines data processing and analysis methods that significantly enhance the personalization of recommendations to meet individual needs. The advantages associated with the integration of artificial intelligence (AI) and machine learning (ML) into Big Data processing to improve CRS efficiency are ...
Added: March 10, 2025
Mustafina N. I., Plaksin M. A., Mikisheva P. A., Proceedings of the Institute for System Programming of the RAS 2024 Vol. 36 No. 2 P. 47–58
The article discusses the issues of planning and resource management in the process of testing
software systems. The paper presents the ACC analysis method used at Google to optimize the distribution of
efforts for testing different parts of the system. Extending the method by adding a fourth characteristic - actors
(roles of system users) – allows for a ...
Added: February 17, 2025
Gorshkov S., Ilyushin E., Chernysheva A. et al., International Journal of Open Information Technologies 2021 Vol. 9 No. 5 P. 12–17
Topic modeling is one of the most widely used methods in text analysis. It can be used to select topics as well as to find the topics distributed in each document from the corpus. In this article, we present a method for clustering communities in the social network VKontakte (the most popular Russian social network) ...
Added: December 25, 2024
Krivonosov M., Nazarenko T., Ushakov V. et al., Technologies 2025 Vol. 13 No. 1 Article 13
This paper introduces a novel approach for classifying multidimensional physiological and clinical data using Synolitic Graph Neural Networks (SGNNs). SGNNs are particularly good forto addressing the challenges posed by high-dimensional datasets, particularly in healthcare, where traditional mMachine lLearning and Artificial Intelligence methods often struggles to find global optima due to the “curse of dimensionality”. To ...
Added: December 23, 2024