Overcoming Multilevel INformation Overload

MSCA (Marie Skłodowska-Curie)HORIZON-TMA-MSCA-SEID: 101086321
EC Contribution
€12,972
Consortium Size
22 orgs
Start Year
2023
Summary

In today's world, access to information thought of as the resolution of uncertainty; is often considered as a benefit or even as an indisputable human right. There is, however, the “dark side” of information: the abundance of data beyond one’s capacity to process them leads to so-called information overload (IOL). This notion had troubled mankind long before even the print was invented and examined from different points of view, ranging from neuroscience to journalism.IOL is, however, usually considered at the individual level by examining a single factor or a specific level that eventually leads to switching off an active individual. The influence of IOL appearing simultaneously at different levels, i.e., a multilevel information overload is unknown, though. These observations lead to setting the main aim of the OMINO - Overcoming Multilevel INformation Overload project in a form of the following objectives:(1) create and apply means to measure multilevel IOL in different systems as well as methods to model IOL and counter-measures to mitigate this phenomenon,(2) training and knowledge exchange on IOL between partners in different domains using expertise from universities in U.S., Singapore and Japan,(3) intersectoral knowledge transfer between academia and the media industry (Slovenian and Austrian Press Agencies) by exposing researchers to real-life problems and giving business access to innovative methods and tools for information analysis.One of the most important aspects of the undertaken research area is its interdisciplinary nature, requiring joint work of experts in different fields and topics, i.e., social sciences, neuroscience, journalism, computing, data mining and complexity science.OMINO will accelerate individual careers of involved researchers, especially early stage ones and increase their employability. The project will lay foundations for long-term collaboration by strengthening existing links between partners and creating new ones.

Consortium (22)

Project Results (49)

Source: CORDIS, the EU research results database.

Publications (44)
Big team science reveals promises and limitations of machine learning efforts to model physiological markers of affective experience
Royal Society Open Science· 2025DOI
Nicholas A. Coles; Bartosz Perz; Maciej Behnke; Johannes C. Eichstaedt; Soo Hyung Kim; Tu N. Vu; Chirag Raman; Julian Tejada; Van-Thong Huynh; Guangyi Zhang; Tanming Cui; Sharanyak Podder; Rushi Chavd
Improving Training Dataset Balance with ChatGPT Prompt Engineering
Electronics· 2025DOI
Mateusz Kochanek, Igor Cichecki, Oliwier Kaszyca, Dominika Szydo, Micha Madej, Dawid Jdrzejewski, Przemysaw Kazienko, Jan Koco
Integrating personalized and contextual information in fine-grained emotion recognition in text: A multi-source fusion approach with explainability
Information Fusion· 2025DOI
Anh Ngo, Jan Koco
Paradise-disorder transition in structural balance dynamics on Erdös-Rényi graphs
Physical Review E· 2025DOI
Krishnadas Mohandas; Krzysztof Suchecki; Janusz A. Hołyst
Peer Interaction Dynamics and Second Language Learning Trajectories During Study Abroad: A Longitudinal Investigation Using Dynamic Computational Social Network Analysis
Language Learning· 2025DOI
Micha B. Paradowski, Nicole Whitby, Micha Czuba, Piotr Brdka
Rank-refining seed selection methods for budget constrained influence maximisation in multilayer networks under linear threshold model
Social Network Analysis and Mining· 2025DOI
Czuba, Michał; Bródka, Piotr
Reference coverage analysis of OpenAlex compared to Web of Science and Scopus
Scientometrics· 2025DOI
Jack H. Culbert, Anne Hobert, Najko Jahn, Nick Haupka, Marion Schmidt, Paul Donner, Philipp Mayr
Supplementary Material from Big team science reveals promises and limitations of machine learning efforts to model physiological markers of affective experience
· 2025DOI
Coles, Nicholas; Perz, Bartosz; Behnke, Maciej; Eichstaedt, Johannes; Kim, Soo Hyung; Vu, Tu; Raman, Chirag; Tejada, Julian; Huynh, Van-Thong; Zhang, Guangyi; Cui, Tanming; Podder, Sharanyak; Chavda,
Temporal Link Prediction in Social Networks Based on Agent Behavior Synchrony and a Cognitive Mechanism
IEEE Transactions on Computational Social Systems· 2025DOI
Yueran Duan; Mateusz Nurek; Qing Guan; Radosław Michalski; Petter Holme
When the crowd gets it wrong – the limits of collective wisdom in machine learning
Scientific Reports· 2025DOI
Orzechowski, Kamil P.; Sienkiewicz, Julian; Fronczak, Agata; Fronczak, Piotr
A Perspective ontheUbiquity ofInteraction Streams inHuman Realm
Lecture Notes in Computer Science, Computational Science – ICCS 2024· 2024DOI
Damian Serwata, Mateusz Nurek, Radosaw Michalski
Bibliometric-Enhanced Information Retrieval: 13th International BIR Workshop (BIR 2023)
Lecture Notes in Computer Science, Advances in Information Retrieval· 2024DOI
Ingo Frommholz, Philipp Mayr, Guillaume Cabanac, Suzan Verberne
Bibliometric-Enhanced Information Retrieval: 14th International BIR Workshop (BIR 2024)
Lecture Notes in Computer Science, Advances in Information Retrieval· 2024DOI
Ingo Frommholz, Philipp Mayr, Guillaume Cabanac, Suzan Verberne
Comparative Analysis of Graph Neural Networks and Transformers for Robust Fake News Detection: A Verification and Reimplementation Study
Electronics· 2024DOI
Soveatin Kuntur, Maciej Krzywda, Anna Wrblewska, Marcin Paprzycki, Maria Ganzha
Deepfake Tweets Automatic Detection
Progress in Polish Artificial Intelligence Research 5. Proceedings of the 5th Polish Conference on Artificial Intelligence (PP-RAI’2024) 18–20.04.2024, Warsaw, Poland, edited by Jacek Mańdziuk, Adam Żychowski, and Mikołaj Małkiński, 194—199· 2024
Adam Frej, Adrian Kamiński, Szymon Szmajdziński, and Piotr Marciniak, Soveatin Kuntur, Wróblewska, Anna
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction
Findings of the Association for Computational Linguistics ACL 2024· 2024DOI
Albert Sawczyn, Katsiaryna Viarenich, Konrad Wojtasik, Aleksandra Domogaa, Marcin Oleksy, Maciej Piasecki, Tomasz Kajdanowicz
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
International Conference on Learning Representations· 2024DOI
Rypeść, Grzegorz; Cygert, Sebastian; Khan, Valeriya; Trzciński, Tomasz; Zieliński, Bartosz; Twardowski, Bartłomiej
Empowering Small-Scale Knowledge Graphs: A Strategy of Leveraging General-Purpose Knowledge Graphs for Enriched Embeddings
LREC-COLING 2024· 2024
Albert Sawczyn, Jakub Binkowski, Piotr Bielak, and Tomasz Kajdanowicz
Evaluating the Effectiveness of Research Grants with Journal Bibliometrics
BIR/ERIC 2023· 2024
Oleksy M., Kazienko P., Dzieżyc M.
Identifying Key Nodes for the Influence Spread Using a Machine Learning Approach
Entropy· 2024DOI
Mateusz Stolarski, Adam Pirg, Piotr Brdka
Mechanistic description of spontaneous loss of memory persistent activity based on neuronal synaptic strength
Heliyon· 2024DOI
Hillel Sanhedrai; Shlomo Havlin; Hila Dvir
Representation Learning inMultiplex Graphs: Where andHow toFuse Information?
Lecture Notes in Computer Science, Computational Science – ICCS 2024· 2024DOI
Piotr Bielak, Tomasz Kajdanowicz
Temporal Link Prediction in Social Networks Based on Agent Behavior Synchrony and a Cognitive Mechanism
arXiv repository· 2024DOI
Yueran Duan, Mateusz Nurek, Qing Guan, Radosaw Michalski, Petter Holme
A deeper look at Graph Embedding RetroFitting
Journal of Computational Science· 2023DOI
Bielak, P., Binkowski, J., Sawczyn, A., Viarenich, K., Puchalska, D., Kajdanowicz, T.
A general model for how attributes can reduce polarization in social groups
Network Science· 2023DOI
Piotr J. Górski; Curtis Atkisson; Janusz A. Hołyst
Automating the Analysis of Institutional Design in International Agreements
Computational Science – ICCS 2023 ISBN: 9783031360237· 2023DOI
Anna Wróblewska; Bartosz Pieliński; Karolina Seweryn; Sylwia Sysko-Romańczuk; Karol Saputa; Aleksandra Wichrowska; Hanna Schreiber
Capturing Human Perspectives in NLP: Questionnaires, Annotations, and Biases
ECAI/NLPerspectives 2023· 2023
Mieleszczenko-Kowszewicz W., Kanclerz K., Bielaniewicz J., Oleksy M., Gruza M., Woźniak S., Dzięcioł E., Kazienko P., Kocoń J.
ChatGPT: Jack of all trades, master of none
Information Fusion· 2023DOI
Kocoń J., Cichecki I., Kaszyca O., Kochanek M., Szydło D., Baran J., Bielaniewicz J., Gruza M., Janz A., Kanclerz K., Kocoń A., Koptyra B., Mieleszczenko-Kowszewicz W., Miłkowski P., Oleksy M., Piasecki M., Radliński Ł., Wojtasik K., Woźniak S., Kazienko
Deep Emotions Across Languages: A Novel Approach for Sentiment Propagation in Multilingual WordNets
2023 IEEE International Conference on Data Mining Workshops (ICDMW)· 2023DOI
Kocoń, Jan
Differential Dataset Cartography: Explainable Artificial Intelligence in Comparative Personalized Sentiment Analysis
Lecture Notes in Computer Science - Computational Science – ICCS 2023· 2023DOI
Jan Kocoń; Joanna Baran; Kamil Kanclerz; Michał Kajstura; Przemysław Kazienko
Disruptive papers in science are losing impact
· 2023DOI
Zeng, An; Fan, Ying; Di, Zengru; Wang, Yougui; Havlin, Shlomo
Domain-Agnostic Neural Architecture for Class Incremental Continual Learning in Document Processing Platform
Computer Science Cornell Univesity· 2023DOI
Mateusz Wójcik; Witold Kościukiewicz; Mateusz Baran; Tomasz Kajdanowicz; Adam Gonczarek
From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysis
2023 IEEE International Conference on Data Mining Workshops (ICDMW)· 2023DOI
Woźniak, Stanisław; Kocoń, Jan
From Generalized Laughter to Personalized Chuckles: Unleashing the Power of Data Fusion in Subjective Humor Detection
SENTIRE/ICDM 2023· 2023
Bielaniewicz J., Kazienko P.
From Generalized Laughter to Personalized Chuckles: Unleashing the Power of Data Fusion in Subjective Humor Detection
2023 IEEE International Conference on Data Mining Workshops (ICDMW)· 2023DOI
Bielaniewicz, Julita; Kazienko, Przemysław
Graph-level representations using ensemble-based readout functions
ICCS 2023· 2023DOI
Binkowski, Jakub; Sawczyn, Albert; Janiak, Denis; Bielak, Piotr; Kajdanowicz, Tomasz
Human-centered neural reasoning for subjective content processing: Hate speech, emotions, and humor
Information Fusion· 2023DOI
Kazienko P., Bielaniewicz J., Gruza M., Kanclerz K., Karanowski K., Miłkowski P., Kocoń J.
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows
SENTIRE/ICDM 2024· 2023
Miłkowski P., Karanowski K., Wielopolski P., Kocoń J., Kazienko P., Zięba M.
Multidimensional attributes expose Heider balance dynamics to measurements
Scientific Reports· 2023DOI
Joanna Linczuk; Piotr J. Górski; Boleslaw K. Szymanski; Janusz A. Hołyst
PALS: Personalized Active Learning for Subjective Tasks in NLP
EMNLP 2023· 2023DOI
Kanclerz K., Karanowski K., Bielaniewicz J., Gruza M., Miłkowski P., Kocoń J., Kazienko P.
RAFEN -- Regularized Alignment Framework for Embeddings of Nodes
ICCS 2023· 2023DOI
Tagowski, Kamil; Bielak, Piotr; Binkowski, Jakub; Kajdanowicz, Tomasz
Similarity-Based Memory Enhanced Joint Entity and Relation Extraction
Lecture Notes in Computer Science ISBN: 9783031360206· 2023DOI
Witold Kościukiewicz; Mateusz Wójcik; Tomasz Kajdanowicz; Adam Gonczarek
The Role ofConformity inOpinion Dynamics Modelling withMultiple Social Circles
Lecture Notes in Computer Science - Computational Science – ICCS 2023· 2023DOI
Stanisaw Stpie; Jarosaw Jankowski; Piotr Brdka; Radosaw Michalski
Towards Model-Based Data Acquisition for Subjective Multi-Label NLP Problems
SENTIRE/ICDM 2023· 2023
Kanclerz K., Bielaniewicz J., Gruza M., Kocoń J., Woźniak S., Kazienko P.
Deliverables (4)
Data Management Plan
Other Results (1)
Periodic Reporting for period 1 - OMINO (Overcoming Multilevel INformation Overload)