Centre for Methodology and Informatics

Assoc. Prof. Dr. Luka Kronegger participated as the keynote speaker at the September Super Znamka Klub event titled Data Intuition as the Superpower of Modern Brands – Data in Branding.

Ljubljana, September 11 – As part of a scientific conference on mentoring relationships and knowledge transfer, a discussion was held on the quality and challenges of doctoral studies in Slovenia. At the center of the debate on successful mentorships were the circumstances of doctoral students and their mentors, which are significantly shaped by factors at the micro or (inter)personal level, at the meso level within the research group and study organization, and at the macro societal level.

Scientific collaborations are an important way for researchers to connect, as they foster the creation and dissemination of new insights. A key role is played by the relationships between doctoral students and their supervisors, as a specific form of scientific collaboration aimed at generating and transferring knowledge within higher education. Research from the project The Supervisory Relationship in the Context of Scientific Collaboration and Knowledge Production, conducted at the Centre for Methodology and Informatics of the Faculty of Social Sciences, University of Ljubljana, shows that successful knowledge transfer depends not only on the interests and motivation of doctoral candidates, but also on the type of relationship supervisors establish with them. In addition to other factors, the successful completion of a doctorate is more likely when a student has more than one supervisor.

In an article published on the N1 Slovenia portal, the head of the center, Prof. Dr. Petrič, spoke about algorithms on social media that are based on offering content tailored to the user's preferences. This creates a bubble in which the content aligns with what the user likes and reinforces their feelings. As a result, this leads to a one-sided perception of opinions, with reduced exposure to diverse information and people with different beliefs, which hinders constructive communication and fosters social conflict.

Exploratory Social Network Analysis with Pajek: Revised and Expanded Edition for Updated Software by Wouter de Nooy (Universiteit van Amsterdam), Andrej Mrvar (University of Ljubljana) and Vladimir Batagelj (University of Ljubljana) is one of the most prominent works dealing with the understanding of social network analysis.

Understanding Large Temporal Networks and Spatial Networks: Exploration, Pattern Searching, Visualization and Network Evolution was published in a series of books on Computational and Quantitative Social Science with Wiley.

Developed in 1996 by Vladimir Batagelj and Andrej Mrvar, Pajek has become an internationally renowned and awarded software enabling analysis and visualisation of large networks.