Building Your Sentiment Analysis Web App with Streamlit: A Practical Guide

Demystifying Sentiment Analysis with Simple Code and Streamlit

Photo by Mirhashim Bagaliyev on Unsplash

In the vast realm of web development, creating applications that can interpret and understand human emotions has become increasingly popular. Sentiment analysis, the art of deciphering sentiments expressed in text, is not only fascinating but also has practical applications in business, social media, and beyond.

In this article, we’ll take you through the process of developing a sentiment analysis web app using Streamlit, a simple and powerful Python library. Let’s dive in!

Getting Started

Before we jump into the code, make sure you have Python installed on your machine. You can install Streamlit using the following command:

pip install streamlit

Now, let’s create a basic structure for our sentiment analysis web app. Open your favorite text editor and create a file named app.py.

# app.py

import streamlit as st

def main():
    st.title("Sentiment Analysis Web App")
    st.subheader("Enter your text below:")

    user_input = st.text_area("Your Text:")
    
    if st.button("Analyze Sentiment"):
        result = analyze_sentiment(user_input)…