Analysis of 2014 South African Elections Twitter Interactions

How political parties and their leaders engage with the public is always an election time fascination of the media and public in general, from photo opportunities to visiting the homes of citizens.

So how can we use Twitter data to measure some of this engagement?

We can track the number of interactions that the leaders have with other Twitter users. For our purpose, an interaction is defined as either a retweet of the party/leaders tweet(s) or a Twitter mention (@partyleader,@partytwitteraccount). Lets look at a timeline of these interactions.

Party Leader Interactions

The leaders I chose to examine are:

There are a lot more political parties in South Africa, but to keep the analysis readable I only examined the ones above due to their prominence.

The good news though is that full dataset is available for anyone to delve into and do more analysis (details at the end of post).

Below are the aggregated interaction counts from the 11th of April to 24 April 2014.

Party Leader Interactions for the past 2 weeks

According to this, it is clear to see that Helen Zille is always the "talk of Twitter town". She dominates with a huge amount of interactions.

On the 24th of April, both Hellen Zille and Julius Malema both started increasing their interactions.
Not all interactions are positive though. More on that later.

Jacob Zuma has low interactions because he rarely uses his Twitter account to interact with users. Especially in matters relating to ANC politics.

Party Twitter Account Interactions

To mirror the above, I examined the following political party Twitter accounts:

The results for the parties are presented below.

Aggregated Political Party Twitter Interactions

In the above graph we see that the political party Twitter accounts are used more by the ANC, DA and EFF. AgangSA is not really getting much interaction.

DA and EFF have been swapping their daily lead in terms of total tweets interaction but ANC is also in there. There is more to explore here but that will be for another day or you can dive in by visiting the data repository detailed at the end of the post.

What causes the fluctuations?

A natural question that arises when looking at the trends is what causes the movements for each Twitter account we are monitoring. For example, if looking at Julius Malema on April 23rd, one notices an increase in total engagement.

This becomes even more evident when analysing the word frequency in the tweets on that day. You can see this in the graph below.

Word Frequencies for 23 April 2014

The histogram even reveals that there was a big conversation around an "open letter". When diving into this it reveals a big topic on that day regarding the below tweet.

Which was the most retweeted tweet in the dataset for the day.

This trend was simple to find and is a good heuristic to use to annotate the original graphs.

But then a next question could be "Are there other people who are garnering more interactions than the politicians on these days?"

The answer is yes.

Here are the top 5 most retweeted on the day (in decreasing order of retweets):

As always there is more that can be done with this data. This is just a taste of what's possible.

Cover Image Credit: Darryn van der Walt

This is a continuation into an analysis dive into South African election related Twitter data. For the first part of this series read Lessons Learnt - South African Elections Social Media Hack

Vukosi Marivate

About Vukosi Marivate

Dr. Vukosi Marivate is a Data Hoarder. Writes in his personal capacity on interesting things we can learn from data. Works for CSIR, ex-intern at Google Inc. PhD, CompSci, Rutgers University (USA)