AI in Social Media Marketing: Using Machine Learning to Analyze Trends and Predict Consumer Sentiment
Bhavana Jamalpur, Somanchi Hari Krishna, Romica Bhat, S. Dharaneesh Prasad, Sourabh Bhattacharya, Dhiraj Kapila · 2025
Social media marketing (SMM) is prominent in the society at present. Individuals use social networking sites to buy different items. The rapid rise of social networking sites has rendered them essential tools for evaluating consumer sentiments and forecasting a wide range of societal and economic patterns. This study gathered statistics from a variety of social media channels. This study examined data to anticipate user activity on social networking sites. This study took into account user statistics from Twitter, LinkedIn, YouTube, Facebook, Instagram, and Pinterest, among other platforms. Because social media networks provide a wide range of statistics at elevated speeds and volumes, predicted big data techniques were applied in this study. This investigation studied user conduct on social networking sites using specific metrics and variables. This study examined user perception and attitudes towards social networking platforms. This study preprocessed data to remove outliers, disturbances, errors, and duplicate records, resulting in high-quality results. As a result, in this paper, an integrated system combining sentiment evaluation and machine learning (ML) methods is constructed. This study utilized computational models and ML to anticipate user conduct on social networking platforms. The framework predicts user conduct on social networking platforms. Eighty percent of data has been employed for training, with twenty percent for testing. After testing many conventional and ensemble ML classifiers, decision trees outscored every other method.