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EC500 Project: Twitter Analyzer

Team Members: Donovan Jones, Luxuan Qi, and Erin Thomas

Project Summary

The goal of this project is to use machine learning and the Twitter API to determine the "mood" of a tweet using keyword analysis and the location of the tweet.

User Stories

  • As someone who works in marketing for a business product, I want to better understand customers' feelings towards a product or brand.
  • As someone who works in politics, I want to keep track of the political viewpoints of the public about important contemporary issues, like gun control.
  • As someone who works in public health, I want to track the spread of epidemics.

Software Architecture & Tech Stack

This application is divided into three components: the geolocation API (geolocation.py), tweet sentiment analyzer (get_tweet_sentiment.py), and front-end visualization (app.py).

Geolocation API

The Geolocation API can obtain the location distribution of users who post Twitter containing keywords. Search for tweets containing keyword to get the addresses of these tweet users. Use geopy to convert the address into latitude and longitude and store it in the list. Use gmplot to mark the latitude and longitude coordinates on the Google map in the form of a heat map. The red areas on the map indicate that there are many people who post Twitter containing keywords. For example, using the keyword BREXIT, we can see on the map that the publisher lives mainly in the UK.

Tweet Sentiment Analysis

Our application analyzes sentiment of Tweets using TextBlob, a natural language processing (NLP) library for processing textual data. It assigns the text a polarity: greater than zero means the sentiment is positive, equal to zero means neutral, and less than zero is negative. We chose this library because it's simple and easy to use for basic sentiment analysis and does not require building test and training data with our own machine learning algorithm.

The get_tweet_sentiment.py file authorizes a Twitter API client, fetches tweets for the input search word using the Twitter API, and then determines each tweet's sentiment as positive, negative, or neutral.

Front-End Data Visualization

Enter the keywords you want to search on the get_tweets webpage, click the button, and after waiting for a while, some of the tweets containing keywords will be displayed on the refreshed page, and the bar graphs of the acquired tweets indicating your mood.

How to Run This Code

  1. Fire up your local terminal and type git clone https://github.com/jonesdebu/EC500-Project-Twitter-Analyzer.git.
  2. Type python3 app.py to run the application.
  3. Navigate to local host http://127.0.0.1:5000/.
  4. Add /get_tweets in your browser bar and enter search words to generate data visualization.
  5. Enter http://127.0.0.1:5000/heatmap to get the generated heat map

References