Sentiment Analysis Using NLP: Visualizing Emotions in Text with Python and Power BI

This article explores how to perform sentiment analysis on a literary text using Natural Language Processing (NLP) in Python, and then visualize the emotional patterns using Power BI.

Details

The article discusses the concept of sentiment analysis, which is the process of determining whether a piece of text expresses a positive, negative, or neutral emotion. This is a widely used technique in NLP, particularly for applications like customer feedback analysis, social media monitoring, and product reviews. In this project, the author applied sentiment analysis to a literary text, 'The Tell-Tale Heart' by Edgar Allan Poe, to understand how emotions evolve throughout the story. The workflow involved loading and cleaning the text, splitting it into smaller segments, applying sentiment analysis using Python's TextBlob library, generating a structured dataset, and then visualizing the results in Power BI. The visualization dashboard showcased emotional trends over time, the distribution of positive and negative segments, and key moments of emotional intensity. This project demonstrates how sentiment analysis using NLP can be applied to creative domains like literature, and how combining NLP with data visualization tools can provide deeper insights into the emotional narrative of a text.