In the contemporary digital age, the proliferation of propaganda and disinformation has emerged as a formidable challenge, particularly in Eastern European societies. These phenomena, fueled by the rapid dissemination capabilities of the internet and social media platforms, have profound implications for the fabric of societies, influencing public opinion, exacerbating social polarization, and undermining trust in democratic institutions. 

The planned two-week scholarly research visit to the University of Tartu represents a strategic initiative to address these challenges through a multidisciplinary approach that integrates social computational science, artificial intelligence (AI) approaches, and big data analysis [1], see Fig. 1.  This visit aimed to foster a collaborative research environment, share experiences, and explore opportunities for international cooperation in combating the adverse effects of propaganda and disinformation [2-9].

Tartu University (TU) Delta's Cutting-Edge Research Environment Fosters Baltic Collaboration. The recently constructed facilities at TU Delta have left a lasting impression, showcasing a modern architectural design that prioritizes the needs of researchers, see Fig. 2. These state-of-the-art buildings, completed just a few years ago, provide an environment meticulously crafted to enhance scientific productivity and spark innovation. One of the most striking features of TU Delta is its diverse and welcoming atmosphere. The research teams comprise scientists from various nationalities, creating a truly global community. This international mix, coupled with an open and friendly culture, has laid a solid foundation for strengthening scientific ties among Baltic Lithuanian, Estonian, and Latvian research groups.

OBJECTIVES AND ACHIEVEMENTS

The visit has paved the way for exciting collaborative endeavors, including:

1. Investigating Propaganda and Disinformation: We established a conceptual research framework to study the social impact of propaganda and disinformation in the Baltic region.
2. International Team Formation: An informal yet actively collaborating research team has been formed, bringing together experts from Vilnius University, University of Tartu, and University of Latvia.
3. Data Collection and Analysis:
   • We designed and conducted a survey across Estonian, Latvian, and Lithuanian populations (N=400 each), gathering both qualitative and quantitative data to assess and model the social impact of propaganda and misinformation.
   • Our teams jointly created databases of propaganda and disinformation articles from each country using LabelStudio. These articles are being analyzed for propaganda techniques, narratives, and other relevant social impact features.
4. Future Collaborations: We've reached a mutual agreement to conduct a comparative study on propaganda and disinformation specifics in the Baltic region. This collaboration aims to produce a high-impact publication in a Web of Science Q1-2 journal, present findings at conferences, and potentially submit later a joint application for a European project.

PERSONAL BENEFITS

The fellowship provided valuable opportunities for professional growth and networking:

1. Enhanced Collaboration: The visit allowed for deeper connections with colleagues from Estonia, particularly at the TU Computer Science Institute in the Delta building.
2. Technical Expertise: Gained experience in adapting LabelStudio for multilingual propaganda and disinformation text markup, organizing international surveys, and collecting data for analysis.
3. Focused Research: The fellowship provided an opportunity for dedicated research and paper preparation.

This visit to TU Delta has not only provided valuable insights into cutting-edge research facilities but has also opened doors for meaningful cross-border scientific cooperation in the Baltic region. The collaborative efforts in studying propaganda and disinformation promise to yield significant contributions to our understanding of these phenomena in Eastern European societies.

POINTS OF REFERENCE

1. D. Plikynas. Systematic overview of machine learning applied for propaganda social impact research. (2024) Proc. at 5th International Conference on NLP & Artificial Intelligence Techniques (NLAI 2024), David C. Wyld, Dhinaharan Nagamalai (Eds) 2024 Computer Science & Information Technology (CS & IT), Vol. 14, No. 22, ISSN : 2231 - 5403. https://airccse.org/csit/V14N22.html 
2. Ahmed, S., Hinkelmann, K., & Corradini, F. (2022). Combining machine learning with knowledge engineering to detect fake news in social networks-a survey. arXiv preprint arXiv:2201.08032
3. Ahsan, M., Kumari, M., & Sharma, T.P. (2019). Rumors detection, verification and controlling mechanisms in online social networks: A survey. Online Soc. Networks Media, 14. https://doi.org/10.1016/j.osnem.2019.100050
4. Choraś, M., Demestichas, K.P., Giełczyk, A., Herrero, Á., Ksieniewicz, P., Remoundou, K., Urda, D., & Woźniak, M. (2020). Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study. ArXiv, abs/2101.01142.
5. Kumar, S., & Shah, N. (2018). False Information on Web and Social Media: A Survey. ArXiv, abs/1804.08559.
6. Abbas, A.M. (2021). Social network analysis using deep learning: applications and schemes. Social Network Analysis and Mining, 11, 1-21. https://doi.org/10.1007/s13278-021-00799-z
7. Ben Chaabene, N.E., Bouzeghoub, A., Guetari, R., & Ghézala, H.H. (2021). Deep learning methods for anomalies detection in social networks using multidimensional networks and multimodal data: a survey. Multimedia Systems, 28, 2133 - 2143. https://doi.org/10.1007/s00530-020-00731-z