Marina Aleksandrova
- Lecturer:Faculty of Social Sciences / School of Sociology / Department of Sociological Research Methods
- Marina Aleksandrova has been at HSE University since 2015.
Continuing education / Professional retraining / Internships / Study abroad experience
Free University of Berlin, Master Programme "Sociology - European Societies" (2016-2017)
Seventh International Summer School "Theory and Methods of Network Analysis" (2017)
III Spring Master's School of MSSES and RANEPA "Sociological Theory and Technology Research" (2015)
Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Researchers" (2022-2023)
Courses (2023/2024)
- Data mining and machine learning in a sociological experiment (Master’s programme; Faculty of Social Sciences; 2 year, 1, 2 module)Rus
- Digital Analytics of Social Processes (Master’s programme; Faculty of Social Sciences; 1 year, 1-4 module)Rus
- Digital Analytics of Social Processes (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Mentor's Seminar "Digital Analytics of Social Processes" (Master’s programme; Faculty of Social Sciences; 1 year, 1-4 module)Rus
- Mentor's Seminar "Digital Analytics of Social Processes" (Master’s programme; Faculty of Social Sciences; 2 year, 1-3 module)Rus
- Probability Theory and Mathematical Statistics (Bachelor’s programme; Faculty of Social Sciences; 2 year, 1 module)Rus
- Past Courses
Courses (2022/2023)
- Probability Theory and Mathematical Statistics (Bachelor’s programme; Faculty of Social Sciences; 2 year, 1 module)Rus
- Research Seminar "Sociology of Business Sphere" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Research Seminar "Sociology of the Public Sphere and Social Communications" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Statistical Analysis (SPSS) (Bachelor’s programme; Graduate School of Business; 3 year, 4 module)Rus
Courses (2021/2022)
- Probability Theory and Mathematical Statistics (Bachelor’s programme; Faculty of Social Sciences; 2 year, 1 module)Rus
- Research Seminar "Sociology of Business Sphere" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Research Seminar "Sociology of the Public Sphere and Social Communications" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Statistical Analysis (SPSS) (Bachelor’s programme; Graduate School of Business; 3 year, 4 module)Rus
Courses (2020/2021)
- Probability Theory and Mathematical Statistics (Bachelor’s programme; Faculty of Social Sciences; 2 year, 1 module)Rus
- Research Seminar "Sociology of Business Sphere" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Research Seminar "Sociology of the Public Sphere and Social Communications" (Master’s programme; Faculty of Social Sciences; 2 year, 1-4 module)Rus
- Statistical Analysis (SPSS) (Bachelor’s programme; Graduate School of Business; 3 year, 3 module)Rus
20234
- Chapter Александрова М. Ю. Возможности и ограничения текст-майнинга: применение современных методов анализа текстовых данных // В кн.: Практики анализа качественных данных в социальных науках. М. : Издательский дом НИУ ВШЭ, 2023. doi Гл. 11. С. 273-312. doi (in press)
- Article Александрова М. Ю. Возможности применения количественного анализа для оценки эффективности в социальной работе: кейс социальных технологий оказания социальной помощи семьям с детьми // Мониторинг общественного мнения: Экономические и социальные перемены. 2023. № 5. С. 26-49. doi
- Book Александрова М. Ю., Говорова А. Д., Нефедова А. И., Полухина Е. В., Рудь Д. С., Савинская О. Б., Стрельникова А. В., Троцук И. В. Практики анализа качественных данных в социальных науках. М. : Издательский дом НИУ ВШЭ, 2023. doi
- Article Ярская-Смирнова Е. Р., Рождественская Е. Ю., Абрамов Р. Н., Борзов С. П., Александрова М. Ю. Социальная технология оказания социальной помощи семьям с детьми: опыт внедрения и оценка эффективности // Мониторинг общественного мнения: Экономические и социальные перемены. 2023. № 5. С. 3-25. doi
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20212
- Article Александрова М. Ю. Методы классификации текстовых данных: можно ли потенциал количественного анализа использовать в качественном исследовании? // ИНТЕРакция. ИНТЕРвью. ИНТЕРпретация. 2021. Т. 13. № 2. С. 81-96. doi
- Article Александрова М. Ю. Методы машинного обучения в социологическом исследовании: предсказание частичного неответа с использованием наивного байесовского классификатора // Мониторинг общественного мнения: Экономические и социальные перемены. 2021. № 1. С. 329-350. doi
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Exploring the Deaf Community: a conference that brought together more than 150 scientists, practitioners and young researchers from different countries and regions of Russia
From May 31 to June 2, 2024, the Second Annual Interdisciplinary Conference “Exploring the Deaf Community” was held, organized by the House of Culture GES-2 together with the International Laboratory for Social Integration Studies of the HSE.
Employees of the IL SIR took part in the presentation of the master's program at the Winter School - 2024
The IL SIR team took part in the presentation of the master’s program “Sociology of the Public Sphere and Digital Analytics” at the Winter School of the HSE Faculty of Social Sciences in Sociology 2024.
Marina Aleksandrova spoke at the conference of the European Sociological Research Association at the University of Milano-Bicocca
Marina Aleksandrova presented at the conference the results of her dissertation research on the topic: “The Application of Natural Language Processing Methods for prediction of item nonresponse: evidence from the ESS”.
Marina Alexandrova took part in the visiting seminar of the academic personnel reserve
Field seminar held from March 31 to April 2, 2023 in the “Voronovo” was dedicated to the possibilities of commercialization of scientific research, the specifics of the search for investments, markets, marketing of scientific research.
Elizaveta Polukhina, Olga Savinskaya and Marina Alexandrova have published chapters in the book «Practices of Qualitative Data Analysis in Social Sciences»
Congratulations to our colleagues on the publication!