feesmustfall

Project description: the fees-must-fall protests took place in South Africa at various university institutions.This project entailed scraping twitter data using an R script, cleaning and sorting data in Excel and creating a Data Visualisation timeline in Tableau.

Overview

I started mining twitter at the end of October 2015 during the #feesmustfall protests using the hashtag “feesmustfall”. The amount of sentiment been shared on the Twitter platform was large and provided one of the most up-to-date sources of the feesmustfall protests. I used R and Tableau to compile this data visualisation. I eventually collected approximately 14,400 unique tweets which were used in the creation of this data visualisation. Whilst every tweet collected in this dataset contained the feesmustfall hashtag, the majority of tweets did not contain more than that. As a result the hashtags used here are from a fraction of the total amount of tweets collected.

Whilst this data visualisation may not provide a complete view of the entire protest, it provides a perspective on the popular hashtags that were used daily. It allows the viewer to pick up on topics that were deemed tweet worthy from the protestors.

One aspect that was noticeable was the use of popular hashtags to boost the chances of tweets been picked up, for example the use of the feesmustfall hashtag been used by twitter users to tweet about completely unrelated tweets. Another aspect that was noticed was the use of combining hashtags of different popular events to boost the chances of tweets been picked up.

Link to Tableau Visualisation