Analyzing the Impact of Green Marketing on Consumer Behavior Using Machine Learning with SVM-Based Sentiment Classification

The effects of green marketing on consumers utilizing machine learning methodologies, with a focus on the SVM for sentiment classification. The increased concern for sustainability and environment-friendly production has put pressure on producers to market their products well. In addition, it proposed SVM model had an 84.6% accuracy, a sentiment divergence of 0.12, and the time taken to process each instance was 3.2ms. The model also demonstrated performance improvements over baseline models: Naïve Bayes had 76.3% accuracy, Random Forest 79.7%, and Neural Network (LSTM) 82.1%. Furthermore, the model was accurate for positive sentiment at 87.5% recall at 89.2%, and implementing an F1-Score of 88.3%. Contrary to other methods of analysis, the model appreciates the complexity of consumer attitudes toward green marketing strategies. Examining how the self-identity of environmentalism has penetrated various aspects of consumers' lives, it makes a useful contribution to practice for firms seeking to target environmentalists effectively in the hope of developing better marketing messages and improving their relationships with this important group in the name of sustainable market practice.