The objective of this project is to build a Business Intelligence dashboard that analyzes social media data to evaluate brand sentiment and public perception. The system will use text analytics and visualization techniques to support marketing strategy, reputation management, and customer engagement decisions.
Collect social media posts or simulated brand review datasets.
Perform text preprocessing including tokenization, stop-word removal, and sentiment scoring.
Store structured sentiment data in a relational database.
Design a data warehouse optimized for sentiment analytics.
Develop dashboards displaying positive, negative, and neutral sentiment trends over time.
Create word clouds and trend visualizations for frequently discussed topics.
Implement classification algorithms to automate sentiment detection.
Compare sentiment performance across regions or campaigns.
Generate alerts for sudden negative sentiment spikes.
Evaluate sentiment model accuracy using performance metrics.
Document analytical findings and explain how BI tools assist brand strategy improvement.
