MSc in Survey Statistics and Data Analytics, ELTE

Congratulations to the winners of the EKÖP (University Excellence Scholarship Program) for the 2026–27 academic year! The recipients include Jakab Buda, our program's instructor (whose research explores changes in parliamentary discourse during changes in government using machine learning-based quantitative data analysis), Blanka Szeitl, instructor (whose research topic is the impact of quota sampling and survey respondent concentration on the reliability of public opinion polls), Dorina Vajda, our part-time instructor and PhD student (representation of the labor market impacts of artificial intelligence in the online press and its measurement using natural language processing), and Márton Polyik, our MSc student in Survey Statistics and Data Analytics (a quantitative analysis of the added value of AI-assisted learning in higher education). Blanka conducts her research at the ELTE Survey Methods Room in Budapest, Jakab and Dorina at the ELTE Research Center for Computational Social Science, and Marci at the ELTE Data for Good research group. We wish them much joy and success in their research!

New publication using computational social science tools, among the authors, Ildikó Barna, Jakab Buda, and Renáta Németh are instructors in the MSc program

Another threat to sound scientific methods: LLMs on the hunt for significance

(PDF) LLMs p-hack LMMs PDF | My recent work has shown that current AI systems help users carry out various types of questionable research practices (QRPs). Building upon the... | Find, read and cite all the research you need on ResearchGate

A new publication has been released, and one of our programme instructors, Renata Nemeth, is among the authors.

We met Viktor Berger at the Hungarian Sociological Association’s conference in Pécs, where both he and we (Renáta Németh, Miklós Szabó) gave presentations on LLMs, and when it turned out that he, too, had been interested in sci-fi as a teenager, we decided to collaborate on a research project - which became the topic of anthropomorphism and LLM use. The results of our joint research have just been published.

This study utilizes a qualitative methodology informed by phenomenology to examine student–machine interactions in higher education, investigating whether students attribute human-like qualities to the machine. Drawing on Edmund Husserl’s concepts of active and passive consciousness, alongside recent phenomenological and anthropological work on AI, we analyze a substantial body of data tracking student–AI tutor interactions across various disciplines using a sociolinguistic approach. Although this humanization may facilitate learning, it raises critical ethical concerns regarding excessive trust - at the end of our paper, we offer several recommendations for future developments.

https://www.sciencedirect.com/science/article/pii/S2772503026000599

Traditionally, awards for the best thesis in each program are presented at the end-of-year graduation ceremony. This year, in the MSc in Survey Statistics and Data Analytics, András Richárd Wernigg's thesis won this title based on the votes of the program's instructors, in a very close competition, as he had excellent competitors. His thesis is a perfect example of how statistics can be of assistance to related disciplines.

András Richárd Wernigg - Application of Monte Carlo Simulation in the Analysis of Healthcare Quality and Risks: A Complex Decision-Support Model Using Hernia Surgery as an Example – ELTE Research Center for Computational Social Science András Richárd Wernigg (LinkedIn) This research examines the quality and accessibility of hernia care in Hungary using stochastic Monte Carlo simulation. The model, based on 2022 baseline data, demonstrates the dangers of deterministic capacity planning and the “error of averages.” The 10-year...

Among the authors two instructors of our MSc program, Zsófia Rakovics and Renáta Németh.

András Richárd Wernigg - Application of Monte Carlo Simulation in the Analysis of Healthcare Quality and Risks: A Complex Decision-Support Model Using Hernia Surgery as an Example – ELTE Research Center for Computational Social Science András Richárd Wernigg (LinkedIn) This research examines the quality and accessibility of hernia care in Hungary using stochastic Monte Carlo simulation. The model, based on 2022 baseline data, demonstrates the dangers of deterministic capacity planning and the “error of averages.” The 10-year...

Dávid Angyalffy - An Analysis of the Language Used on index.hu Following the 2020 Change in Ownership Using Machine Learning Methods – ELTE Research Center for Computational Social Science Dávid Angyalffy (LinkedIn, GitHub, E-mail) The polarization of the Hungarian online media landscape and the quantitative assessment of changes in editorial policy are current issues in digital journalism research. This study analyzes whether a change in the language of the Index.hu portal can be de...

Levente Kander - The Application of Contrastive Learning to Tabular Data on Patients with Aortic Valve Stenosis – ELTE Research Center for Computational Social Science Levente Kander This thesis attempts to more accurately map the patterns underlying tabular data from patients with aortic valve stenosis by applying a self-supervised contrastive learning technique, thereby facilitating the creation of a more robust patient segmentation. First, we present the theore...

Exciting experiments at our institute.