Abstract
Social media platforms have become a rich source of user-generated content, and analyzing the sentiments expressed in these platforms provides valuable insights for businesses, political campaigns, and social research. AI-driven neural networks, particularly deep learning models, have shown great promise in sentiment analysis tasks. These models can effectively process large amounts of unstructured text data, identify emotions, and classify sentiments with high accuracy. This article explores the use of neural networks for sentiment analysis in social media, focusing on applications, challenges, and future trends in the integration of AI technologies into sentiment analysis systems.
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