Twitter Sentiment Analysis

Built with:

• React
• Node
• DatumBox Sentiment API
• Google Sentiment API

Positive hashtag example:

Negative hashtag example:

Username example:

Description:

Analyze tweet sentiment using an username or hashtag using two sentiment APIs. I originally created this app a couple years ago but it is tested on:

Node 12.18.2 Npm 6.14.7

The live app is running on Herkoku and can be tried out at: https://salty-journey-93853.herokuapp.com/

Requirements

In order to run this app, you will need to sign up for the following free APIs:

1. The Datumbox Machine Learning API: https://www.datumbox.com/machine-learning-api/

2. The Google Natural Language Processing API: https://cloud.google.com/natural-language/docs/basics

3. The Twitter API https://developer.twitter.com/en/docs

After signing up for the APIs, create a file called 'config.js' in the repository root with the following API credentials:

const config = { twitter: { consumer_key: '', consumer_secret: '', access_token: '', access_token_secret: '' }, google: { "apiKey" : '' }, datumBox: { "apiKey" : '', }, port: process.env.PORT || 3000 };

module.exports = config;

To change ports or HOST to a live URL edit the .env file

Usage

1. Install dependencies and run the app from the root directory:

   cd NodeTwitterSentiment
   npm install
   npm start

API requests will be visible via terminal output

2. Go to http://0.0.0.0:3000/ to see the App

TODO: Average sentiments from both APIs and render on front end Dockerfile Get All Tweets