My News

A News app with Sentiment analysis, Recommendations and Data Visualization.

Overview

A React frontend for my backend service and REST API which polls popular RSS news feeds for articles and performs sentiment analysis on headlines and descriptions.

Main Features

• Classify news articles with their sentiment score from 1 to -1, positive/neutral/negative.

  • Tokenized with BERT transformer, then classified with a regression neural network (NN) to output sentiment scores between 1 and -1.

• Recommendation system using OpenAI text embeddings - filter by semantically similar articles

  • Generates a joint text embedding of article titles, genre, description which is stored in a Pinecone vector database
  • Similar embeddings are queried and ranked based on the cosine distance between these vectors.

• User voting system for sentiment, inspired by hotukdeals and Reddit

• Articles filtering by metadata - sentiment rating, source and topic.

• Anonymous commenting / discussion.

• Data visualization with MongoDB Charts

Tech used

• MongoDB
• React
• Redux
• Mantine React Framework
• FastAPI
• Python transformers
• Pinecone - vector database

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Backend

Article headlines and descriptions are given a positivity score between -1 and 1. The model used is based on BERT, via the transformers python package.

Sentiment results are stored with article metadata on a MongoDB database which is exposed to the web app.

Installation and Usage

Requires nodejs, my RSS feed sentiment analysis service and a MongoDB database to store news articles.

1. Run the web server locally npm run start

2. Start the backend service to collect news articles, see the linked repository.