Social Order and Chaos in the 2017 UK Elections

The results of the 2017 General Election have come as a shock to the UK; Labour has defied expectations and pre-election opinion polls, leaving the UK with a hung parliament. The huge conversation on social media gives us an insight into opinion, patterns and voter behaviour on a large scale.

We tracked social dialogues and sentiments during the election to get insights in the driving forces behind the changes in the political landscape in the UK, and to see what hidden patterns we can identify within the enormous volumes of related chatter.

For this report, we limited ourselves to Twitter as an information source and all data was collected via our flagship STORY platform on a non-tweaked standard set-up. To capture all relevant Tweets -independent of volume and speed- we used Twitter's/Gnip's Firehose for harvesting.

General Patterns When preparing this we obviously didn't know what was going to happen or what volumes and patterns to expect, so we started by simply tracking a few typical hashtags in the days leading up to the event and kept doing this until the whole circus was over.

The figure below shows the evolution of the usage of hashtag #GE2017 on Twitter from 2 to 8 June with the time in CEST (i.e., UK time + 1:00).

From this figure alone we can already identify some interesting patterns:

Tensions were slowly rising the days before the election. The peak on the night before the election was at least twice as high as a few days earlier and the daily volume had already tripled.

From this picture, it seems as if the London terror attacks on the night from 3-4 June did not affect the elections at all. No special pattern is visible on or immediately after the events.

In the UK, no numbers/predictions are published in the media until the doors of the polling stations have closed, so on election day itself, Twitter volumes were higher than usual, but still very much under control, averaging around 10 Tweets/sec.

This changed dramatically the moment the doors had closed and the first exit polls were published, predicting a disastrous outcome for the Conservative party. Within seconds, Twitter volumes Skyrocketed and when scrutinising the feeds, we found individual seconds with over 200 election-related Tweets. The average volume over the first full hour after closing time was 3 times that of the hour before.

The impact of the first predictions was so large that Twitter even forgot to go to bed: the usual day-night pattern was completely distorted and it took another 24 hour for a normal UK night to set in again.

We found it hard to believe that the London terror attacks had no effect on people's sentiment around the elections, so we dug into this a little deeper. We correlated #GE2017 occurrences with various other keywords and found the following interesting pattern when looking for enough or resign among the #GE2017 Tweets:

Clearly, sentiments trended on at least 3 occasions, not seen in the global patterns:

On Sunday 4 June enough occurrences had a sharp peak and after little investigation, we found that this was the direct result of just 1 Tweet going viral, namely this one: WATCH: Police have had enough and accuse Theresa May of outright lies. Tory cuts have made us all less safe #GE2017 pic.twitter.com/sqTrKEJq88

- Scott Nelson (@SocialistVoice) June 4, 2017 Remarkably and unexpectedly, this Tweet was Retweeted faster and more often than people quoted Theresa May's own Enough is enough statement.

On Monday 5 June resign suddenly trended, and this turned out to be the direct result of Corbyn's statement where he asked for May's resignation and accused her of cutting police budgets while she was home secretary. Jeremy Corbyn says he would back calls for Theresa May to resign over cuts in police numbers https://t.co/iyjwAVrmJc #GE2017 pic.twitter.com/iF5hV65JTv

- BBC Breaking News (@BBCBreaking) June 5, 2017

On Friday 9 June resign trended again for almost the complete day: immediately after the first exit polls were made public, around her speech for winning her district, the moment the first morning news shows were broadcast on radio/TV and finally around lunch when she announced not to step down and to form a coalition.

It is remarkable that individual Tweets with such an enormous impact can start to trend so suddenly and be shared on a large scale so quickly (we're talking minutes here). There lies enormous value in having the right toolset so that key events such as these can be identified at an early stage, while still having sufficient time for analysis and/or appropriate actions. Obviously appropriate actions' may mean something completely different for a journalist, a TV producer or a political campaign leader

Patterns in Party Loyalty We also tracked social volumes attributed to explicit support of one of the participating parties. For each political party, we monitored occurrences of #Vote, where is either the party name/abbreviation (e.g. #VoteLabour) or the party's main candidate (e.g. #VoteMay), and of course various variations and alternative spellings. For a culture that's known and often praised for its reserved nature, people in the UK turned out to surprisingly forthcoming when it came to sharing their political support online. This led to a steady flux throughout the day of 10 Tweets/sec in which people called out their support.

The pattern found while tracking specific party loyalty this was extremely one-sided, see the figures below:

Three conclusions are obvious:

Labour (pink) was leading the social arena, with no other party coming even close. In fact, each other party collected less than 10% of Labour's volume and added together the others didn't even reach 25% of Labour.

Although being the leading party when it comes to the popular vote, the Conservatives

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