All work

A news reader that scores every article for polarity and subjectivity with TextBlob.
Role
Personal project
Type
Full-Stack
Status
Shipped
Source
News Sentiment Platform4 layers
React UIExpress.jsPythonTextBlobPostgreSQL

Overview

A personal project that pulls in news articles, runs each one through Python and TextBlob to score how positive and how subjective it is, and stores the results in PostgreSQL. The React and Tailwind front end shows each article with its scores. Fetching, scoring and display are separate layers, so the scoring step can change without touching the rest.

At a glance

scores per article: polarity and subjectivity
2
scores per article: polarity and subjectivity
separate layers: fetching, scoring, display
3
separate layers: fetching, scoring, display

System sketch

ClientAPIAnalysisDataReact UIExpress.jsPythonTextBlobPostgreSQL

A simplified view of how the main parts connect.

What I built

  1. Real-time sentiment analysis with polarity and subjectivity scoring

  2. Responsive React and Tailwind front end

  3. RESTful API integration for news data

  4. PostgreSQL database for persistent storage

  5. Sentiment scores shown alongside each article

Stack

  • React
  • Express.js
  • Python
  • PostgreSQL
  • TextBlob
  • Tailwind CSS

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