AI Can Predict Student Academic Performance Based on Social Media Subscriptions
A team of Russian researchers, including scientists from HSE University, used AI to analyse 4,500 students’ subscriptions to VK social media communities. The study found that algorithms can accurately identify both high-performing students and those struggling with their studies. The paper has been published in IEEE Access.
Every person leaves behind a digital footprint—likes, photos, music listening habits, and clicks on links—so even the most cautious users can be profiled based on their online activity. Some people believe they do not need to manage their digital footprint, as they assume that social media information cannot affect their professional or personal lives. Yet for scientists, publicly available data on people’s online activity provides valuable material for research.
A team of researchers from HSE University, Skoltech, and Tomsk State University (TSU) collected data on VK community subscriptions from 4,445 students with publicly available profiles. Then, using natural language processing (NLP) techniques, the researchers classified the topics of these social media communities, assessed the complexity of the texts students read, and analysed the emotional tone of the content. They then compiled a digital profile for each student, capturing their preferences and interests. Afterward, the researchers used machine learning to explore the relationship between students’ online activity and their academic performance.
The researchers developed an algorithm that predicts academic performance by analysing students’ online community subscriptions. In particular, high-performing students are more likely to subscribe to science and education communities that discuss new technologies and publish analytical articles. High achievers also tend to read more complex texts and show greater interest in discussions and in-depth analyses of information.
In contrast, their low-performing peers are more likely to subscribe to entertainment communities focused on humour, memes, music, and video games. The content in these communities expressed more negative emotions and was also less informative than the content favoured by top performers.
Sergei Gorshkov
'Some of the results surprised us. For example, students interested in art or travel tend to perform exceptionally well academically. These hobbies do not interfere with their studies—in fact, they seem to enhance academic performance. In contrast, active engagement with communities related to side jobs is associated with lower academic achievement, which is understandable,' comments Sergei Gorshkov, Doctoral Student at the School of Data Analysis and Artificial Intelligence of the HSE Faculty of Computer Science.
Educational institutions can use this approach to identify talented applicants and tailor their curricula to specific groups. Additionally, subscription analysis can assist employers in recruiting candidates with strong analytical abilities.
Dmitry Ignatov
'This study serves as yet another reminder of the importance of digital hygiene. For example, when signing contracts to open a bank account or with a mobile operator, you may be asked to grant permission to access information from social network accounts linked to your phone number. This data can later be used to create your digital profile. Whether or not you want this to happen is up to you,' says Dmitry Ignatov, Head of the Laboratory for Models and Methods of Computational Pragmatics at the HSE Faculty of Computer Science.
This work is part of an open data study supported by the University Consortium of Big Data Researchers and approved by the Ethics Committee of the TSU Faculty of Psychology.
See also:
Researchers Examine Student Care Culture in Small Russian Universities
Researchers from the HSE Institute of Education conducted a sociological study at four small, non-selective universities and revealed, based on 135 interviews, the dual nature of student care at such institutions: a combination of genuine support with continuous supervision, reminiscent of parental care. This study offers the first in-depth look at how formal and informal student care practices are intertwined in the post-Soviet educational context. The study has been published in the British Journal of Sociology of Education.
HSE Scientists: Social Cues in News Interfaces Build Online Trust
Researchers from the HSE Laboratory for Cognitive Psychology of Digital Interface Users have discovered how social cues in the design of news websites—such as reader comments, the number of reposts, or the author’s name—can help build user trust. An experiment with 137 volunteers showed that such interface elements make a website appear more trustworthy and persuasive to users, with the strongest cue being links to the media’s social networks. The study's findings have been published in Human-Computer Interaction.
Immune System Error: How Antibodies in Multiple Sclerosis Mistake Their Targets
Researchers at HSE University and the Institute of Bioorganic Chemistry of the Russian Academy of Sciences (IBCh RAS) have studied how the immune system functions in multiple sclerosis (MS), a disease in which the body's own antibodies attack its nerve fibres. By comparing blood samples from MS patients and healthy individuals, scientists have discovered that the immune system in MS patients can mistake viral proteins for those of nerve cells. Several key proteins have also been identified that could serve as new biomarkers for the disease and aid in its diagnosis. The study has been published in Frontiers in Immunology. The research was conducted with support from the Russian Science Foundation.
Scientists Develop Effective Microlasers as Small as a Speck of Dust
Researchers at HSE University–St Petersburg have discovered a way to create effective microlasers with diameters as small as 5 to 8 micrometres. They operate at room temperature, require no cooling, and can be integrated into microchips. The scientists relied on the whispering gallery effect to trap light and used buffer layers to reduce energy leakage and stress. This approach holds promise for integrating lasers into microchips, sensors, and quantum technologies. The study has been published in Technical Physics Letters.
HSE Scientists Test New Method to Investigate Mechanisms of New Word Acquisition
Researchers at the HSE Centre for Language and Brain were among the first to use transcranial alternating current stimulation to investigate whether it can influence the acquisition of new words. Although the authors of the experiment have not yet found a link between brain stimulation and word acquisition, they believe that adjusting the stimulation parameters may yield different results in the future. The study has been published in Language, Cognition and Neuroscience.
Twenty vs Ten: HSE Researcher Examines Origins of Numeral System in Lezgic Languages
It is commonly believed that the Lezgic languages spoken in Dagestan and Azerbaijan originally used a vigesimal numeral system, with the decimal system emerging later. However, a recent analysis of numerals in various dialects, conducted by linguist Maksim Melenchenko from HSE University, suggests that the opposite may be true: the decimal system was used originally, with the vigesimal system developing later. The study has been published in Folia Linguistica.
Scientists Rank Russian Regions by Climate Risk Levels
Researchers from HSE University and the Russian Academy of Sciences have assessed the levels of climate risks across Russian regions. Using five key climate risks—heatwaves, water stress, wildfires, extreme precipitation, and permafrost degradation—the scientists ranked the country’s regions according to their need for adaptation to climate change. Krasnoyarsk Krai, Irkutsk Region, and Sverdlovsk Region rank among the highest for four of the five climate risks considered. The study has been published in Science of the Total Environment.
HSE Researchers Teach Neural Network to Distinguish Origins from Genetically Similar Populations
Researchers from the AI and Digital Science Institute, HSE Faculty of Computer Science, have proposed a new approach based on advanced machine learning techniques to determine a person’s genetic origin with high accuracy. This method uses graph neural networks, which make it possible to distinguish even very closely related populations.
HSE Economists Reveal the Secret to Strong Families
Researchers from the HSE Faculty of Economic Sciences have examined the key factors behind lasting marriages. The findings show that having children is the primary factor contributing to marital stability, while for couples without children, a greater income gap between spouses is associated with a stronger union. This is the conclusion reported in Applied Econometrics.
Fifteen Minutes on Foot: How Post-Soviet Cities Manage Access to Essential Services
Researchers from HSE University and the Institute of Geography of the Russian Academy of Sciences analysed three major Russian cities to assess their alignment with the '15-minute city' concept—an urban design that ensures residents can easily access essential services and facilities within walking distance. Naberezhnye Chelny, where most residents live in Soviet-era microdistricts, demonstrated the highest levels of accessibility. In Krasnodar, fewer than half of residents can easily reach essential facilities on foot, and in Saratov, just over a third can. The article has been published in Regional Research of Russia.