SPARCK LABS Data visualisation

Using Data Science to predict Brexit

In 2016, we teamed up with our Data Science colleagues to track how the EU Referendum polled on Twitter, both for Leave and Remain, with interesting results!

Twitter data in the week up to the referendum, including on polling day, clearly showed a bias towards Leave, contrary to most traditional polls.

 

The base tool that we used was configured in just 3 days to analyse the data and present the findings live. It scaled to over 150 tweets/second! See for yourself and interact with the graphs below to see how sentiment changed over time, and how turbulent the Referendum night itself was.

Average Sentiment on Polling Day

REMAIN

LEAVE

Sentiment Over Time

 

Count of tweets

During run up to the EU Referendum, we wanted to use the public’s opinion across the globe to see if it was possible to create a low cost, realtime, analytics engine. We took the concept from idea to live in less than 10 working days.

The tool is a reusable solution that organisations can customise to their needs: it’s low cost, easy to use and quick to deliver. Organisations can leverage the power of Big Data and Social Media by themselves, without the need to engage expensive digital agencies. We set out to see if we could quickly and cheaply disrupt this market.

In under 2 weeks, and for less than £10K, we built a re-useable solution that can be set up within a few hours to monitor and display the results of a realtime event.‍

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