Political Opinion Finder

This is my 3rd year BSc Computer Science Degree Dissertation project. It involves a program that collects Tweets from twitter, analyses them using natural language to calculate their political opinion so it can then be compared general populace opinions from pollster data.

Motivation

The motivation of this project is to investigate into the difference between political opinions shared on online social media to the opinions of the general populace (opinions gathered from pollsters data) by using natural language and big data analyse.

Findings

The findings of the investigation can be found in the paper I wrote on Academia. The TLDR was that majority of Twitter users did side with remain. I go into further detail on why in the paper.

Installation

Clone the repo, install Python 3 and the following Python libraries using pip install:

Tweepy Twitter API library for accessing Twitter
pymongo MongoDB library for using MongoDB
codecs Encoding library for encoding the tweets
nltk Natural language library for analysing meaning of tweets
tqdm

Install the following from their .whl from the Windows Binary site using pip install:

numpy
scipy
scit_learn
sklearn

This is for Windows(I believe they work with normal pip install on Linux).

Create a JSON file with users MongoDB server credentials, use the example file as a guide. If using a local server download MongoDB and leave mongoURL empty in the JSON file.

User must also create a JSON file with there Twitter API credentials, use the example file as a guide.

Operation

Run the following in console/terminal:

python ./main.py

Then select what you would like to do from the menu presented to you.

On first run the program will download the necessary NLTK data (This may take some time). It is advised to use Gather tweets option on first run so there are tweets in the database. The calculation of twitter vs poll opinion difference does take a long time (can be hours on a slower system).