Machine Learning Techniques for Social Media Data Analytics

 Week 1 - Introduction

·         Overview of social media platforms and data characteristics (structured vs. unstructured)

·         Importance and challenges of analyzing social media data

·         Basics of machine learning and its role in social media analytics

·         Typical ML pipeline for social media applications

Week 2 - Data Collection & Data Acquisition

·         Data collection methods (APIs, web scraping, streaming data)

·         Demo on Data collection methods

·         Demo on Data Acquisition from open repositories

Week 3 - Introduction to Natural Language Processing

·         Basic NLP Pipeline

·         Text Preprocessing

·         Text Normalization

·         Feature Extraction

·         Demo on NLP Workflow

Week 4 - Machine Learning Modeling – Supervised Learning I

·         Supervised learning fundamentals

·         Classification techniques for social media data

·         Evaluation: accuracy, precision, recall, F1-score

·         Demo

Week 5 - Machine Learning Modeling – Supervised Learning II

·         Regression Algorithms

·         Feature Engineering for Regression

·         Evaluation Metrics

·         Demo

Week 6 - Machine Learning Modeling – Unsupervised Learning

·         Clustering Approaches

·         Topic Modeling

·         Evaluation Metrics

·         Demo

Week 7 - Advanced Applications in Social Media Analytics

·         Sentiment analysis

·         Fake news detection

·         Abusive Comments detection

·         Trend prediction

·         Recommendation systems

Week 8 - Case Studies & Ethics

·         Detecting AI-generated product reviews

·         Political Multiclass Sentiment Analysis of Twitter Comments  

·         Abusive Comment Detection from Social Media Data

·         Ethical considerations, privacy concerns, and future trends in AI-driven social media analytics