Analysis of Machine Learning Classifiers’ Efficacy for Social Media Ads Classification
Ravi Sharma, Prerna Varshney, Deepanshi Srivastava, Km. Bharati · 2024
Different sectors of society are using social media more. Much user-generated content is published daily. In social media advertising, corporations want to maximize ROI and reach their target demographic. Not all products or services are suited for everyone, depending on age and finances. Analysis of social media advertising's content is essential for categorizing it. This study determines which client segments are most likely to buy the advertised goods or services, maximizing profits. The classifier allows detailed competition analysis and can affect social media marketing. Modern technologies for social media ad analysis and categorization can improve client segmentation and engagement. According to performance measures, the Random Forest Classification model predicts the target variable better than the Logistic Regression and Decision Tree Classifier models. Machine learning may optimize resource allocation and target audience engagement in marketing tactics, improving consumer responsiveness.