Development of a system for determining the emotional tone of posts on social networks

Abstract

In the rapidly evolving landscape of social media, emotional analysis stands as a pivotal area of exploration. This article delves into the realm of emotional analysis in social networks, focusing on the development and evaluation of methods for real-time determination of emotional tone in posts. The study begins with an introduction to the significance of emotional analysis in social media, addressing pertinent challenges and outlining research objectives.

            The research methodology encompasses a thorough review of existing emotional analysis methods in social media, with a detailed exposition of the proposed methodology for real-time emotional tone determination. Special emphasis is placed on the selection and preprocessing of data, incorporating advanced machine learning algorithms.

The article presents the outcomes of experiments designed to assess the effectiveness of the proposed methods. Results are discussed in the context of their applicability to various types of content within social networks, and comparative analyses are drawn against existing methodologies. The data and analyses provided serve as a foundation for understanding the current state of emotional analysis in social media and offer prospects for future research directions.

            In conclusion, the article summarizes the key findings, highlighting the efficacy of the proposed methods in real-time emotional analysis. It underscores the significance of ongoing collaboration between researchers and practitioners to further advance the field of emotional analysis in social media.