MODELS FOR PREDICTING CHANGES IN PUBLIC OPINION DURING THE IMPLEMENTATION OF THE NARRATIVE IN SOCIAL MEDIA
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Relevance. In the modern world, social media are becoming the main channels of communication, which significantly affects the formation of public opinion and the implementation of strategic narratives. In the context of global information challenges, in particular war, understanding and predicting changes in public sentiment is extremely important for the effective implementation of state information policy, as well as for combating disinformation. The subject of the study is modeling the processes of predicting changes in public opinion during the implementation of a strategic narrative through social media. The aim of the study is to analyze the effectiveness of using diffusion of innovations models and neural networks to predict changes in socio-political sentiment, as well as to optimize content strategy on social media platforms. Main results: The study showed that social media has a significant impact on public consciousness, and the use of information dissemination models, such as Bass's diffusion of innovations model, allows predicting the spread of narratives among different groups of users. The use of neural networks to analyze socio-political sentiment provided highly accurate forecasts with good quality indicators. The results of the study emphasize the importance of adapting content strategy in social media to increase the effectiveness of influencing the audience. Conclusion. The results obtained confirm that for the successful implementation of the state's strategic narrative, it is necessary to apply combined methods of forecasting and adapting content on social platforms. Successful adaptation of content strategy, taking into account changes in user behavior and trends in socio-political sentiment, is a key factor for effective influence on public opinion and support of national interests in the digital environment.
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