BrandLens.AI – NLP-Powered Social Media Analytics Framework for Sentiment and Engagement Intelligence

With social media playing a central role in brand communications and customer engagement, it is crucial for businesses to analyze social media data effectively to optimize their marketing strategies. Traditional analysis methods are often labor-intensive and limited in scope. This project focuses on developing a comprehensive social media analytics framework powered by NLP and machine learning to conduct brand sentiment analysis, monitor engagement metrics, and generate actionable insights for marketing teams.

 Week 1-2: Initial Planning and Requirement Analysis

Define the objectives, scope, and high-level requirements of the project

Accumulate the needed data and resources  Week 3-4: Data Collection and Preparation Phase

Gather multi-platform social media data from their APIs

Clean and pre-process the data for analysis  Week 5-6: Sentiment Analysis and Topic Modeling Phase

Develop NLP models for sentiment and topic modeling

Train the model on the social media data collected  Week 7-8: Dashboard Development Phase

Design and develop a dashboard to visualize key metrics and insights

Integrate NLP models with data visualization tools.

 Weeks 9-10: Testing and Refinement Phase

Extensive testing for accuracy and reliability

Refine the system given the performance metrics and user feedback.

 Weeks 11-12: Final Evaluation and Reporting

Final evaluation and validation of the system.

Final project report and documentation compilation

Individual report presentations by students