1. Psychological aspects in retrieval and recommendationMarkus Schedl, Elisabeth Lex, Marko Tkalčič, 2025, published scientific conference contribution abstract Abstract: Psychological processes play a critical role in shaping users’ inter- actions with information retrieval (IR) and recommender systems (RS). Therefore, understanding human cognition, decision-making, and emotions is vital to enable user-centric retrieval and recommendation systems. Vice versa, understanding whether these aspects are also present in the systems themselves (e.g., in training data, ranking models, or outputs), or even injecting them on purpose, can inform the development of psychology-inspired systems. The purpose of this tutorial is to provide its attendees with an introduction to psychological concepts that are important in the ecosystem of search, retrieval, and recommendation, in particular, cognitive architectures, cognitive effects and biases, as well as personality and affect. Leveraging corresponding models allows its audience to build or refine psychology-informed IR and RS technology. The interdisciplinary tutorial requires intermediate expertise in terms of IR and RS, while we do not assume knowledge in psychology.
Keywords: recommender systems, emotions, personality
Published in RUP: 08.04.2026; Views: 60; Downloads: 7
 Full text (954,00 KB)
This document has more files! More... |
2. Prompt to press : evaluating human perception of AI involvement in news writing across prompt specificityUroš Sergaš, Ahmadou Wagne, Thomas Elmar Kolb, Julia Neidhardt, Bruce Ferwerda, Marko Tkalčič, 2026, published scientific conference contribution Abstract: Large language models (LLMs) are becoming a common feature in content creation tools, prompting important questions about how design choices influence user trust and engagement in AI- assisted journalism. Beyond output quality, factors such as prompt specificity, model choice, and authorship disclosure are themselves interaction design parameters that influence how users interpret and evaluate AI contributions. Yet, little is known about how these design decisions affect reader perceptions in journalistic contexts. To address this gap, we conducted an experiment with 150 participants who evaluated news articles on the sensitive topic of assisted suicide. The articles systematically varied in authorship (human-written, AI-edited, or AI-generated), stance (pro- or anti- legalization), and prompt specificity (vague, moderate, or highly detailed). Participants rated each article on engagement, subjectivity, and perceived AI involvement, and also provided open-ended justifications for their authorship judgments. Our findings show that prompt specificity and model choice significantly influence perceptions of authorship, underscoring how technical design decisions in AI tools can shape public trust in journalism.
Keywords: AI-generated news, prompt specificity, human vs. AI detection, media perception, assisted suicide
Published in RUP: 24.03.2026; Views: 232; Downloads: 11
Full text (593,55 KB)
This document has more files! More... |
3. Designing the ideal political identity questionnaire using machine learning and ideology scalesAna Nikolić, Uroš Sergaš, Marko Tkalčič, 2025, published scientific conference contribution (invited lecture) Abstract: Political ideology shapes beliefs, behavior and attitudes toward society. Many existing questionnaires for measuring ideology are lengthy, repetitive, and misaligned with self-perception. This paper investigates whether a shorter, reliable, two-dimensional political identity questionnaire can be created using machine learning and psychometric methods. Sixty participants completed four ideological instruments (MFQ, SDO, RWA and 8values). Lasso regression and Random Forest with nested cross-validation identified predictive items, while psychometric evaluation included CFA and Cronbach’s alpha. Random Forest outperformed Lasso. Internal reliability was excellent and factor loadings supported a two-factor structure despite moderate model it. Findings show that ideology can be measured efficiently with reduced items, supporting applications in research, digital platforms and political psychology.
Keywords: political ideology, questionnaire design, machine learning, psychometrics
Published in RUP: 30.01.2026; Views: 340; Downloads: 2
Full text (189,01 KB) |
4. Analiza vpliva tehnologije na kakovost spanja : zaključna nalogaTamara Mikač, 2025, undergraduate thesis Keywords: kakovost spanja, modra svetloba, tehnologija, spalna rutina, življenski slog, napovedni modeli, stres, diplomske naloge
Published in RUP: 14.10.2025; Views: 667; Downloads: 100
Full text (1,20 MB) |
5. |
6. |
7. |
8. |
9. |
10. |
