More Twitter Users Want to Split with EU and Support #Brexit

Our study suggests the #BRexit referendum is anything but close, with a clear preference among Twitter users for leaving the EU. Ontotext analysed over 1.5 million tweets related to the referendum up until 13 May 2016.

Download full Twitter analysis on #Brexit for free now

The Source

They were identified by common referendum-related terms, such as #brexit; #StrongerIn; “uk eu vote”, and then analysed for the use of hashtags, cited , and general sentiment for leaving or remaining in the EU.

94.4% of the selected tweets were in English (i.e. English is the language predicted by Twitter’s algorithm for language detection). Below is the distribution of the other languages:

brexit map

More details about the Twitter data as well as links to actual data files are available in the full version of “#Brexit Twitter Analytics” report.

The Output

We looked at users with the biggest number of posts in our dataset, also considering their polarity. At a first glance, it appears that most of them are not public figures or media companies (see the figure below).

Propagandistic Twitter users are the most influential, in terms of number of posts and number of retweets. They are dominating the top of the list. It would be interesting to find out which are the actors behind these propagandistic users, whether they are politicians, parties, organisations, etc.

brexit wordcloud

We went further to look at the users mentioned in tweets, by frequency and by polarity of the context. The number of retweets a Twitter user receives is a pretty strong gauge of their influence on the wider conversation. According to this analysis, the top five most re-tweeted Twitter users on the topic of the EU referendum are all Leave campaigners.

Download full Twitter analysis on #Brexit for free now

The same analysis as above was conducted for publishing domains frequently cited in the tweets. E.g., a tweet can cite an article from bbc.co.uk in support of their statement.

The big question is whether someone’s activity on Twitter forms an accurate indication of their likelihood to go out and vote on the day. We’ll find out soon.

Laura Tolosi

Laura Tolosi

Senior Data Scientist at Ontotext
Laura is an enthusiastic data scientist, always searching to improve semantic technologies with latest machine learning tools. She believes that merely extracting patterns from big data should not be the ultimate goal of predictive modelling, but understanding why certain patterns occur and thus provide with an understanding of causality.
Laura Tolosi

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