On November 26–28, 2025, the 11th edition of the Scientific Conference on Business Informatics “IwZ 2025” was held at the Faculty of Management of the University of Łódź. The main theme of this year’s edition, “Digital Transformation – (R)evolution in Management”, reflected current research trends in the field of business informatics. Three representatives of the Department of Information Systems participated in the conference: Dr. Elżbieta Lewańska, Dr. Piotr Stolarski, and Izabela Czumałowska.
Dr. Elżbieta Lewańska presented a paper entitled “From Data to Sustainable Development: An ESG Event Taxonomy in Business Process Analysis”, co-authored with Dr. Milena Stróżyna. The paper addressed the automation of non-financial ESG indicator analysis in organizations, made possible by combining the proposed ESG event taxonomy with process mining tools.
Izabela Czumałowska presented a paper entitled “Wikipedia Neutrality Across Languages: A Comparison of Article Sentiment Using Language Models”, prepared together with Dr. Włodzimierz Lewoniewski and Dr. Milena Stróżyna. The paper focused on comparing the sentiment of articles of different quality levels and thematic categories using selected language models for analysis. The study helps determine whether articles in the analyzed language versions of Wikipedia comply with the principle of a neutral point of view (NPOV).
Dr. Piotr Stolarski presented two papers. The first, entitled “Identification and Analysis of Articles Related to Blockchain and Cryptocurrencies in Different Language Versions of Wikipedia”, was prepared jointly with Dr. Włodzimierz Lewoniewski. The study concerned multilingual knowledge extraction from Wikipedia and Wikidata using graph analysis, category mapping, and semantic properties. Using blockchain and cryptocurrencies as examples, it demonstrated differences in content representation across 16 language versions and highlighted the potential of this approach for knowledge management and information retrieval systems.
The second paper presented by Dr. Stolarski was entitled “Evaluation of OCR Methods and Vision–Language Models in Detecting Disinformation in Social Media Images”. The study compared the effectiveness of classical OCR tools and modern AI models in analyzing visual content such as memes. The results showed that hybrid solutions combining OCR with large language models significantly improve the quality of text extraction, which is crucial for disinformation detection systems in social media.