pm990320 / twitter-emotions

Web Science Coursework

Twitter Scraper and Emotion Analysis

Patrick Menlove - 2250066M

This code is part of an academic assignment of Web Science - University of Glasgow.

Setup

You can use conda to create a virtualenv with all required dependencies

conda env create -f environment.yml

The example also uses Docker to run a MongoDB instance with the sample data.

docker-compose up -d

If you would like to run the save_tweets.py file to ingest new tweets, you will need to set up the .env file with the following environment variables, corresponding to the Twitter API credentials

TWITTER_CONSUMER_KEY
TWITTER_CONSUMER_SECRET
TWITTER_ACCESS_TOKEN
TWITTER_ACCESS_TOKEN_SECRET

Instructions on Running (for Marker)

If you would like to use the sample data, do not run save_tweets.py as this will begin appending to the dataset and may skew the values.

The flow of execution then should be:

1. process_tweets.py
2. data_stats.py
3. prune_data.py
4. analyse_crowdsource.py

All data is inspectable under the data/ path. If the MongoDB data archive does not work, the tweet data used is also supplied in csv format in this path.