CURRENT RESEARCH OF INFORMATION INFLUENCES IN SOCIAL NETWORKS
DOI:
https://doi.org/10.28925/2663-4023.2025.27.716Keywords:
social networks; information influence; disinformation; cybersecurity; information security; information management, neural networks, user behavior.Abstract
Modern social networks play a significant role in shaping public opinion and spreading information flows. With the development of artificial intelligence and machine learning technologies, the ability of platforms to influence the perception of information and user behavior has increased. The article highlights the results of modern research in the field of information influences, in particular disinformation, manipulative content and their impact on society. The main areas of analysis are outlined, including the mechanisms of disinformation dissemination, the role of social platforms, the use of artificial intelligence to detect manipulation, as well as the psychological, technical and legal aspects of counteraction. This article analyzes current research on the management of information influences in social networks, considering the capabilities of neural networks to identify and analyze influences that can cause irregular changes in user behavior. Particular attention is paid to the use of AI and neural networks to automate the detection of fake content, the study of social network algorithms and the fight against destructive information campaigns in the context of hybrid warfare. Prospects for further research are considered, including the development of adaptive AI models, the creation of regulatory mechanisms for regulating the information space and the study of the impact of information "bubbles". The paper also examines social and cognitive factors that contribute to the spread of manipulative content, taking into account cultural contexts. It is concluded that the constant development of disinformation creation technologies emphasizes the need for an interdisciplinary approach to its research. The results obtained contribute to the development of effective tools for ensuring information security on a global scale and create the basis for further innovations in this area.
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References
World Economic Forum. (2024). The Global Risks Report 2024. Retrieved from https://www3.weforum.org/docs/WEF_The_Global_Risks_Report_2024.pdf
Scopus. (n.d.). Influence of social networks [Search results]. https://www.scopus.com/results/results.uri?sort=plf-f&src=s&st1=Influence+social+networks&sid=2e9da1c4c0f6c0ad01f9ba4611b01431&sot=b&sdt=b&sl=40&s=TITLE-ABS-KEY%28Influence+social+networks%29&origin=searchbasic
Bakshy, E., Rosenn I., Marlow C., & Adamic L. (2012). The role of social networks in information diffusion. In: Proceedings of the 21st international conference on World Wide Web (WWW ‘12). Association for Computing Machinery, 519–528. https://doi.org/10.1145/2187836.2187907
Acemoglu, D., Ozdaglar, A., & ParandehGheibi, A. (2010). Spread of (mis)information in social networks. Games and Economic Behavior, 70(2), 194–227. https://doi.org/10.1016/j.geb.2010.01.005
Cordasco, G., Gargano, L., & Rescigno, A. A. (2019). Active influence spreading in social networks. Theoretical Computer Science, 764, 15–29. https://doi.org/10.1016/j.tcs.2018.02.024
Abd Al-Azim, N. A. R., Gharib, T. F., Hamdy, M., & Afify, Y. (2022). Influence propagation in social networks: Interest-based community ranking model. Journal of King Saud University - Computer and Information Sciences, 34(5), 2231–2243. https://doi.org/10.1016/j.jksuci.2020.08.004
Chen, W., Castillo, C., & Lakshmanan, L. V. S. (2013). Information and influence propagation in social networks. Morgan & Claypool Publishers.
Zheng, X., Zhong, Y., & Zeng, D. et al. (2012). Social influence and spread dynamics in social networks. Front. Comput. Sci. 6, 611–620. https://doi.org/10.1007/s11704-012-1176-1
Govindankutty, S., & Gopalan, S. P. (2024). Epidemic modeling for misinformation spread in digital networks through a social intelligence approach. Sci. Rep. 14. https://doi.org/10.1038/s41598-024-69657-0
Tomassi, A., Falegnami, A., & Romano, E. (2024). Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society. PLoS ONE 19(5). https://doi.org/10.1371/journal.pone.0303183
Ittan, M. E., Elayidom, S. M., & Mathew, M. P. (2025). The Social Media Influence Journey: A Comprehensive Study of Techniques and Strategies for Effective Diffusion. Enhancing Communication and Decision-Making With AI. IGI Global. https://doi.org/10.4018/979-8-3693-9246-1.ch003
Bartal, A., & Jagodnik, K. M. (2021). Role-aware information spread in online social networks. Entropy, 23(11), 1542. https://doi.org/10.3390/e23111542
Kumar, S., Mallik, A., Khetarpal, A., Panda, B.S. (2022). Influence maximization in social networks using graph embedding and graph neural network. Information Sciences, 607, 1617–1636. https://doi.org/10.1016/j.ins.2022.06.075
Gong, Y., Shang, L., & Wang, D. (2024). Integrating social explanations into explainable artificial intelligence (XAI) for combating misinformation: Vision and challenges. IEEE Transactions on Computational Social Systems, 11(5), 6705–6726. https://doi.org/10.1109/TCSS.2024.3404236
Parthiban, G., Germanaus, A. M., & S. John Peter. (2024). A Hybrid Approach for Integrating Deep Learning and Explainable AI for augmented Fake News Detection. Journal of Computational Analysis and Applications (JoCAAA), 33(06), 299–308.
Kumar, S., Mallik, A., & Panda, B.S. (2023). Influence maximization in social networks using transfer learning via graph-based LSTM. Expert Systems with Applications, 212. https://doi.org/10.1016/j.eswa.2022.118770
Guinote, A., Kossowska, M., Jago, M., Idenekpoma, S., Biddlestone, M. (2025). Why do people share (mis)information? Power motives in social media. Computers in Human Behavior, 16. https://doi.org/10.1016/j.chb.2024.108453
Bian, T., Xiao, X., Xu, T., Zhao, P., Huang, W., Rong, Y., & Huang, J. (2020). Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 34(01), 549–556. https://doi.org/10.1609/aaai.v34i01.5393
Statista. (2024). Daily time spent on social networking by internet users worldwide from 2012 to 2023 [Graph]. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/
Zhang, C., Fan, C., Yao, W., Hu, X., & Mostafavi, A. (2019). Social media for intelligent public information and warning in disasters: An interdisciplinary review. International Journal of Information Management, 49, 190–201. https://doi.org/10.1016/j.ijinfomgt.2019.04.004
Liu, Y., & Wu, Y. F. (2018). Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1).
Kanavos, A., & Livieris, I. E. (2020). Fuzzy information diffusion in Twitter by considering user’s influence. International Journal on Artificial Intelligence Tools, 29(5). https://doi.org/10.1142/S0218213020400035
Montanari, A., & Saberi, A. (2010). The spread of innovations in social networks. Proceedings of the National Academy of Sciences, 107(47), 20196–20201. https://doi.org/10.1073/pnas.1004098107
Yang, K.-C., Varol, O., Davis, C. A., Ferrara, E., Flammini, A., & Menczer, F. (2019). Arming the public with artificial intelligence to counter social bots. Human Behavior and Emerging Technologies, 1(1), 48–61. https://doi.org/10.1002/hbe2.115
Meel, P., & Vishwakarma, D. K. (2020). Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges, and opportunities. Expert Systems with Applications, 153. https://doi.org/10.1016/j.eswa.2020.112986
Ratkiewicz, J., Conover, M., Meiss, M., Goncalves, B., Flammini, A., & Menczer, F. (2021). Detecting and Tracking Political Abuse in Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 297–304. https://doi.org/10.1609/icwsm.v5i1.14127
Sadiku, M. N. O., Ashaolu, T. J., & Ajayi-Majebi, A. (2021). Artificial intelligence in social media. International Journal of Scientific & Engineering Research, 2(1), 15–20.
Benabdelouahed, R., & Dakouan, C. (2020). The use of artificial intelligence in social media: Opportunities and perspectives. Expert Journal of Marketing, 8(1), 63–72.
Fernandez-Luque, L., & Imran, M. (2018). Humanitarian health computing using artificial intelligence and social media: A narrative literature review. International Journal of Medical Informatics, 114, 64–70.
Nunavath, V., & Goodwin, M. (2018). The Role of Artificial Intelligence in Social Media Big data Analytics for Disaster Management-Initial Results of a Systematic Literature Review. Proceedings of the 5th International Conference on Information and Communication Technologies for Disaster Management, IEEE. https://doi.org/10.1109/ICT-DM.2018.8636388
Ozbay, F. A., & Alatas, B. (2020). Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Statistical Mechanics and its Applications, 540. https://doi.org/10.1016/j.physa.2019.123174
Kaplan, A. (2020). Artificial intelligence, social media, and fake news: Is this the end of democracy? In Media & Society, Westminster Research, 165–180.
Thuraisingham, B. (2020). The role of artificial intelligence and cyber security for social media. 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). https://doi.org/10.1109/IPDPSW50202.2020.00184
Babu, N. V., & Kanaga, E. G. M. (2022). Sentiment analysis in social media data for depression detection using artificial intelligence: A review. SN Computer Science, 3(1), 1–15. https://doi.org/10.1007/s42979-021-00958-1
Hajli, N., Saeed, U., & Tajvidi, M. (2022). Social bots and the spread of disinformation in social media: The challenges of artificial intelligence. British Journal of Management, 33(1), 45–62. https://doi.org/10.1111/1467-8551.12554
Shao, C., Ciampaglia, G., Varol, O., Flammini, A., & Menczer, F. (2017). The spread of fake news by social bots. arXiv. https://doi.org/10.48550/arXiv.1707.07592
Surjatmodjo, D., Unde, A. A., Cangara, H., & Sonni, A. F. (2024). Information pandemic: A critical review of disinformation spread on social media and its implications for state resilience. Social Sciences, 13(8). https://doi.org/10.3390/socsci13080418
Bradshaw, S. (2020). Influence operations and disinformation on social media. https://www.cigionline.org/articles/influence-operations-and-disinformation-social-media/?utm_source=twitter&utm_medium=social&utm_campaign=ai-series
Buchanan, T. (2020). Why do people spread false information online? The effects of message and viewer characteristics on self-reported likelihood of sharing social media disinformation. PLoS ONE 15(10). https://doi.org/10.1371/journal.pone.0239666
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic literature review on the spread of health-related misinformation on social media. https://www.sciencedirect.com/science/article/pii/S0277953619305465
Shu, K., Bhattacharjee, A., Alatawi, F., Nazer, T. H., Ding, K., Karami, M., & Liu, H. (2020). Combating disinformation in a social media age. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(6). https://doi.org/10.1002/widm.1385
Hajli, N., Saeed, U., Tajvidi, M., & Shirazi, F. (2021). Social Bots and the Spread of Disinformation in Social Media: The Challenges of Artificial Intelligence. British Journal of Management, 33. https://doi.org/10.1111/1467-8551.12554
Waszak, P. M., Kasprzycka-Waszak, W., & Kubanek, A. (2018). The spread of medical fake news in social media – The pilot quantitative study. Health Policy and Technology, 7(2), 115–118. https://doi.org/10.1016/j.hlpt.2018.03.002
Litvinchuk, I. S. (2023). Disinformation in Social Networks: Counteraction Algorithms. Scientific Notes of the Taras Shevchenko National University of Crimea, 1, 29–34. https://doi.org/10.32782/2710-4656/2023.1.2/29
Martsenyuk, M.S., & Kozachok, V. A. (2023). Analysis of Methods for Detecting Disinformation in Social Networks Using Machine Learning. Cybersecurity, 2, 12–18.
Vova, V. O. (2024). The Spread of Fake News and Disinformation Regarding the War in Ukraine Through Social Networks Telegram and TikTok. Young Scientist, 3, 56–60.
Kalnybolotska, E. V. (2022). Ensuring Information Security in Ukraine’s Social Networks in the Context of Full-Scale Military Aggression. Public Administration, 5, 45–52.
Makarova, O. P., & Zinchenko, D. A. (2024). Analysis of Methods for Detecting and Countering Propaganda and Disinformation in Social Networks in Ukraine. Bulletin of the Kyiv National University of Trade and Economics, 6, 194–199.
Kitsa, M. O. (2016). Fake Information in Ukrainian Social Media: Concepts, Types, Influence on Audience. Scientific Notes of the Ukrainian Academy of Printing, 1.
Kotykhova, L. D. (2022). Research on the Use of IT to Counter the Spread of Russian Disinformation in the Media Space During the War. Bulletin of the Pryazovskyi State Technical University, 4.
Hargoun, Y., Tulupnikov, D. (2024). Propaganda and Disinformation in Russian and Ukrainian Media: Information Technologies in Conflict. Acta de Historia & Politica: Saeculum XXI, 4.
Kuznetsova, O. (2024). Signs of Russian Disinformation Created by AI in Internet Media and Social Networks. Journal of Lviv Polytechnic National University, 12, 79–89. https://doi.org/10.23939/sjs2024.01.079
Marushchak, A. I. (2022). Prerequisites for the Formation of Legal Mechanisms to Counter Disinformation in Social Media in the Context of National Security. Information and Law, 4.
Dragovoz, V. Y. (2022). Counteracting Disinformation and Fake News in the Information Environment of Ukraine. Information Technologies, 6.
Hulak, H. M., Zhiltsov, O. B., Kyrychok, R. V., Korshun, N. V., & Skladannyi, P. M. (2024). Information and cyber security of the enterprise. Textbook. Lviv: Publisher Marchenko T. V.
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Copyright (c) 2025 Олександр Ткаченко, Анна Ільєнко, Олександр Улічев, Єлизавета Мелешко, Лілія Галата
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