Web-Based Sentiment Analysis with Plotly: A Practical Guide

Unlock the Power of Data Visualization for Sentiment Analytics

Photo by KOBU Agency on Unsplash

In today’s data-driven world, sentiment analysis has become a crucial tool for businesses and organizations to gauge public opinion, monitor brand reputation, and make informed decisions. While there are various tools and libraries available for sentiment analysis, creating an interactive and visually appealing dashboard can greatly enhance the value of your insights.

In this article, we’ll explore how to develop a web-based sentiment analysis dashboard using Plotly, a powerful data visualization library for Python.

Setting the Stage

Before we dive into the code, let’s ensure we have the necessary dependencies installed. We’ll be using the following libraries:

• Plotly: A high-level, declarative charting library for Python
• NLTK (Natural Language Toolkit): A popular library for natural language processing tasks
• Pandas: A data manipulation and analysis library

You can install these libraries using pip:

pip install plotly nltk pandas

Preparing the Data