Brexit on Twitter Week Ending 21st May
Part one of two, part two here:
Overview
The following analysis uses social network analysis methodology created by Right Relevance - more information in this post.
The network map of the Twitter conversation during the week shows the a clear polarisation as might be expected.
Here is the visualisation of the conversation based on ReTweets.
The colours show communities of users detected by machine learning algorithms. At this level just a simple split between Leave & Remain is detected.
A slightly more nuanced version shows various sub communities within these two main groups.
A very different picture of the conversation emerges if the connections include Mentions and Replies as well as Retweets.
Here is the network map including Mentions which shows that there is a significant amount of conversation between the two groups whilst still a clear separation of the two main positions.
There is a contrast between the two sides in terms of the volume of communication. However, there is also a very significant difference in the type of communication.
That is illustrated in the following network map.
Here you can clearly see that the Leave side is made up of fewer major influencers with a large and noisy following of users simply echoing those major players.
The remain side is made up of a much larger number of important Users with much less noise and a more sophisticated interaction between a diverse collection of interests.
Tables of Performance
The following tables show which Users have been the most influential on Twitter during the week ending 21st May.
Overall
Vote Leave
Remain
