- Laboratory Head:Institute of Education / Centre for Contemporary Childhood Research / Laboratory of Computational Social Sciences
- Lecturer:Institute of Education / Department of Educational Programmes
- Ivan Smirnov has been at HSE since 2014.
Education and Degrees
Candidate of Sciences* (PhD)
Master's in Interdisciplinary Approaches to Life Science
University of Paris 7
Degree in Applied Mathematics and Computer Science
Saint Petersburg State University
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
- International Conference on Computational Social Science (Эванстон). Presentation: Gender Bias in Sharenting
- XVIII April International Academic Conference on Economic and Social Development (Москва). Presentation: School Segregation in the Digital Space
- International Conference on Computational Social Science (Кельн). Presentation: School Segregation in the Digital Space
- 9th International Conference on Social Informatics (Оксфорд). Presentation: The Digital Flynn Effect: Complexity of Posts on Social Media Increases over Time
- eStars2017 (Москва). Presentation: Online education and inequality reproduction
- VIII Международная конференция Российской ассоциации исследователей высшего образования (РАИВО) (Москва). Presentation: Cultural capital in the digital space and university choice
- 2016VII Международная конференция Российской ассоциации исследователей высшего образования (РАИВО) (Москва). Presentation: Формирование гомофилии по академической успеваемости среди студентов
- Международный симпозиум "Л.С. Выготский и современное детство" (Москва). Presentation: Сегрегация школьников в виртуальном пространстве
- Открытая научно-практическая конференция молодых исследователей EDgeneration (Москва). Presentation: Новые данные и их значение для исследований образования
Dissertation for a degree of Candidate of Science
- Article Sivak E. V., Smirnov I. Parents mention sons more often than daughters on social media // Proceedings of the National Academy of Sciences of the United States of America. 2019. Vol. 116. No. 6. P. 2039-2041. doi
- Chapter Smirnov I. Predicting PISA Scores from Students’ Digital Traces, in: PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON WEB AND SOCIAL MEDIA. American Association for Artificial Intelligence (AAAI) Press, 2018. P. 360-364.
- Preprint Smirnov I. Schools are segregated by educational outcomes in the digital space / Cornell University. Series Computer Science "arxiv.org". 2018.
- Article Smirnov I., Thurner S. Formation of homophily in academic performance: Students change their friends rather than performance // Plos One. 2017. Vol. 12. No. 8. P. 1-16. doi
- Chapter Smirnov I. Identifying Factors Associated with the Survival and Success of Grassroots Educational Innovations, in: Reforms and Innovation in Education - Implications for the Quality of Human Capital / Ed. by A. M. Sidorkin, M. Warford. Springer, 2017. doi P. 85-98.
- Chapter Smirnov I. The Digital Flynn Effect: Complexity of Posts on Social Media Increases over Time, in: Social Informatics. SocInfo 2017. Lecture Notes in Computer Science, vol 10539. Springer, Cham. Springer, 2017. P. 24-30. doi
The round table on ‘Psychological Wellbeing in the Digital Age’ brought together a range of scholars and one industry professional to talk about how a user’s digital footprint—or ‘digital traces’—can be used to discern a person’s psychological state, predict their behavior, and, potentially, even improve their psychological wellbeing.
IOE researchers Elizaveta Sivak and Ivan Smirnov have analyzed over 60 million public posts on VK, the most popular Russian social networking site, to discover that both men and women mention sons more often than daughters. They have also found that posts featuring sons receive 1.5 times more likes. The results have been published in the Proceedings of the National Academy of Sciences of the United States of America.
Sons are more popular than daughters on social media
On September 11, Ivan Smirnov, graduate of the HSE Institute of Education doctoral programme, defended his Candidate of Sciences (Education) on ‘Differentiation of students by academic performance in a social network’. His thesis consists of four articles which had been published in academic journals, as well as a description of the study methods, design and main outcomes.
A recent study by IOE expert Ivan Smirnov shows that students’ academic achievement can be predicted from their ‘digital traces.’
Several academic papers by leading experts at the HSE Institute of Education have been featured in Springer’s newly released volume Reforms and Innovation in Education, edited by Alexander M. Sidorkin and Mark K. Warford. The authors explore various factors and processes shaping the relationships between educational reforms, as driven by deep and progressive socioeconomic changes, their effects on innovations across the educational realm, and the implications for the quality of human capital.
A paper co-authored by IOE expert Ivan Smirnov, which explores how academic achievement shapes students’ peer relationships, and namely friendship networks as suggested by social media data, has recently been published on PLOS One.
A study by IOE doctoral scholar Ivan Smirnov, which analyzes developments in the complexity of social network messages, has recently received broad coverage by science & research news desks at leading international media. Ivan’s contribution takes us some steps closer to understanding what drives the evolution of social media texting practices and whether the argument about networking sites undermining language literacy and future life achievement actually holds water, MIT Technology Review and The Times say.
On January 15–18, the HSE Institute of Education doctoral student and junior researcher Ivan Smirnov took part in the NetSci-X International Conference on Network Science.