Social Media Analytics (NLP) Training Course

This course provides participants with the knowledge and tools to analyze social media data using Natural Language Processing (NLP). It focuses on extracting insights from unstructured text, understanding customer sentiment, detecting trends, and measuring brand performance. Participants will gain hands-on experience with NLP techniques and social media analytics tools to enhance digital marketing, brand management, and customer engagement strategies.

Target Groups

• Digital marketing professionals
• Social media managers and analysts
• Data scientists and NLP practitioners
• Business intelligence professionals
• Customer experience and CRM teams
• PR and brand management specialists
• Students in marketing, data science, or communication studies

Course Objectives

By the end of this course, participants will be able to:

• Understand the role of NLP in social media analytics.
• Collect and preprocess social media data from multiple platforms.
• Apply text mining and NLP techniques for sentiment and opinion analysis.
• Detect trends, emerging topics, and brand mentions.
• Classify, cluster, and visualize social media text data.
• Use predictive models to forecast social media trends and engagement.
• Integrate NLP analytics into digital marketing strategies.
• Apply ethical standards in handling social media data.
• Leverage open-source NLP tools and APIs for analysis.
• Deliver actionable insights for brand and business decisions.

Course Modules

Module 1: Introduction to Social Media Analytics and NLP

• Importance of social media analytics in business strategy
• Basics of Natural Language Processing (NLP)
• Structured vs. unstructured data in social media
• Case studies of NLP applications in social media marketing

Module 2: Social Media Data Collection

• APIs for Twitter (X), Facebook, Instagram, LinkedIn, and TikTok
• Web scraping techniques for social platforms
• Data extraction tools (Tweepy, BeautifulSoup, Selenium)
• Ethical and legal considerations in social data collection

Module 3: Text Preprocessing for NLP

• Tokenization, stopword removal, and stemming/lemmatization
• Handling emojis, hashtags, and slang in social media text
• Dealing with noisy, multilingual, and short-form text
• Data cleaning and preparation pipelines

Module 4: Sentiment Analysis in Social Media

• Lexicon-based vs. machine learning-based sentiment analysis
• Tools and libraries (VADER, TextBlob, Hugging Face Transformers)
• Measuring brand perception through sentiment scores
• Visualizing sentiment trends over time

Module 5: Topic Modeling and Trend Detection

• Extracting themes using LDA and NMF models
• Identifying emerging hashtags and viral topics
• Trend detection through keyword and frequency analysis
• Tracking competitor mentions and industry trends

Module 6: Text Classification and Opinion Mining

• Supervised classification of social media posts
• Detecting positive/negative/neutral opinions
• Fake news and spam detection in social platforms
• Application of deep learning models (CNNs, RNNs, BERT)

Module 7: Customer Insights and Engagement Analysis

• Analyzing customer feedback and reviews
• Mapping customer journeys using NLP
• Identifying influencers and opinion leaders
• Audience profiling from social media conversations

Module 8: Visualization and Reporting of Social Media Data

• Dashboards for social media analytics (Power BI, Tableau)
• Word clouds, trend graphs, and sentiment maps
• Automated reporting with Python and R
• Best practices in presenting social insights to stakeholders

Module 9: Predictive Analytics in Social Media

• Predicting campaign engagement and virality
• Forecasting brand reputation shifts
• Social network analysis and influence modeling
• Applying NLP for predictive customer behavior

Module 10: Case Studies and Practical Applications

• Real-world social media analytics projects
• Hands-on analysis with Python NLP libraries (NLTK, spaCy, Hugging Face)
• Integrating NLP into CRM and digital marketing platforms
• Future trends in NLP-driven social media analytics