Blog Post

Tweeting Brexit: Narrative building and sentiment analysis

Public discourse on social media was already in favour of Brexit by early summer 2015, and stayed that way until the referendum. An analysis of more than 890 000 tweets posted since 2012 reveals clear trends in the mood of online discussion. Our new methodology captures something that betting odds and opinion polls were not able to reveal – but will it be useful in future elections?

By: and Date: November 16, 2016 European Macroeconomics & Governance Tags & Topics

On 7 May 2015 David Cameron was re-elected on a platform that included a promise to hold a referendum on the UK’s EU membership. A few weeks later, at the European Summit of 25-26 June, Cameron set out his EU renegotiation aims at a meeting dominated by the Greek debt and refugee crises.

Within this short time-span the amount of tweets on Brexit-related subjects jumped from around 1000 per week to 5000, which reached 10 000 if we consider retweets.

The number of related hashtags continued to rise during the following month, reaching more than 15 000 during the hot month of the refugee crisis (figure 1).

Figure 1 – Counts over time: 2015

figure1

That peak was not just a momentary event, but set the tone for the rest of the time leading up to the referendum. The flow of Brexit-related Twitter activity remained strong until the vote, with clear jumps at the announcement of the referendum on 20 February 2016 and the launch of the official campaigns on 15 April 2016.

Activity then increased steadily in the final two months of the campaign, with over 100 000 Tweets per week by the end of May 2016 (figure 2).

Figure 2 – Counts over time: 2016 without June

figure-2

Sentiment analysis and mood switches

Using the extracted tweets, we performed a sentiment analysis in cooperation with the Dortmund Center for data-based Media Analysis (DoCMA).

Sentiment analysis applies natural language processing, text analysis and computational linguistics to identify and extract subjective information in a corpus of source material. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic, or the overall stance of a document.

This attitude may be the speaker’s/writer’s judgment or evaluation, affective state, or the intended emotional communication. Assessing a statement as positive or negative requires analysis of the words and phrases used, as well as their grammatical and discursive context. This measurement is known as contextual polarity.

In this case, we applied a novel three-stage approach developed at DoCMA. First, two human coders carried out a traditional sentiment analysis coding a sample of 1500 Tweets. In a second step, a list of sentiment words was extracted from this sample to calibrate a sentiment-metering algorithm which was consequently applied to the vast majority of the Tweets.

This semiautomatic approach is an innovative work-in-progress, whose reliability needs further clarification. Therefore, the sentiment analysis of these Brexit tweets needs to be treated with a certain degree of caution. In-depth results are due to be published in the coming months. However, initial results are promising and our findings concerning the Brexit debate appear convincing.

Figure 3 – Mean sentiment scores by week

figure-3

Figure 3 depicts the results by showing the overall mood in the “Twittersphere” over time. Values of zero represent a balanced view where tweets containing a predominantly pro-Brexit (positive values) and a pro-Remain stance (negative values) offset each other.

Most of the first half of 2015 was characterized by a slight bias towards the Remain position (negative values). The results change drastically in the summer of 2015, when the trend shifts considerably towards exiting the EU (positive territory in the graph). This is then where the values stay throughout the period until the referendum in June 2016.

Let’s consider two key-findings briefly.

First, the swing is associated with the refugee crisis that started grabbing the public’s attention in the summer of 2015. This was one of the most important issue driving the Brexit debate. Immigration had been a hotly debated issue in the UK before, with conservative politicians pushing for the imposition of a limit to the influx of foreigners, even from EU countries. The severity of the refugee crisis, which set in motion more than a million refugees from war-torn countries such as Syria and Afghanistan, aggravated an already sceptical public opinion. The Twitter analysis supports the hypothesis that the immigration issue fired up the debate on whether or not to leave the EU.

Second, once the overall mood has moved into pro-Brexit territory, it stays there for the remaining period. Even though values decline from an initial peak in July 2015, the high level of persistence of overall sentiment is remarkable. A predominately Brexit-favouring mood seems to be reinforced by the dynamics of social media. In particular, key Brexit activists who were highly visible on Twitter gathered ever-higher levels of attention. Sentiment in the Twittersphere proves to be enduring, a result we have encountered in other debates as well. Therefore, social media seems to reproduce (rather than disrupt) a hierarchical public discourse sphere.

The other story: Betting odds and opinion polls

Betting odds and opinion polls clearly did not catch the amplitude of the mood switch visible in the sentiment analysis. Until the very last moment, these traditional political predictors were consistently showing a tendency to remain, albeit with some fluctuation. At the most, they envisaged the possibility of a very tight result, but the fairly strong result for leave was a genuine shock.

Figure 4 – Probability of Brexit according to betting odds

figure-4

This indicator tracks the average implied probability of the event ‘UK Leaving the EU’, based on bookmaker quotes available on the Oddschecker website.

Figure 5 – UK EU Referendum Voter Intention

figure-5

The Bloomberg Composite Indicator of UK EU Referendum Voter Intention Surveys takes the average of polls data from various surveys including BMG, ComRes, ICM, Ipsos MORI, ORB, Survation and YouGov.

Classic polling has proved rather incorrect in other recent cases as well. Donald Trump’s victory in the US presidential elections was not foreseen by the vast majority of polls. However, his huge social media presence, most notably on Twitter, told a different story.

Conclusions – What do we learn?

Twitter can be considered a novel type of elite media that enables agenda setters to communicate directly with other agenda setters and a politically active part of the public (Boynton & Richardson 2016).

Whoever gets sufficient attention in the Twittersphere can count on his or her messages being taken up by traditional media, thereby boosting the senders’ reach and potentially influencing public opinion on a broader scale.

Emotionality, negativity and occasionally breaking taboos help to raise attention in social media environments.Donald Trump and the Brexiteers can serve as paragons for this transmission channel. If their views dominate the public debate, they may have a significant influence on voting behaviour.

They can especially prime those voters who have not come to a definitive decision on who or what to vote for – or even whether to vote at all – until shortly before election day. In elections or referenda where large parts of the electorate remain undecided, or unsure if to vote at all, polls may not suffice to capture the public’s mood.

It is therefore not far-fetched to argue that sentiment analyses of tweets may offer useful new early indicators for public opinion. In particular, this should be the case when debates entail clearly distinct poles. If decisions are to be taken either for or against a certain policy, or if candidates represent the wings of a bipolar political system, Twitter analysis should be of particular value.

In traditional parliamentary elections, however, where parties compete through complex programs on a wide range of policies, social media analysis in this form looks less promising for the prediction of election outcomes.

The authors would like to thank Gerret von Nordheim of TU Dortmund University/Dortmund Center for data-based Media Analysis for his highly valuable support in conducting the Twitter analysis.


Republishing and referencing

Bruegel considers itself a public good and takes no institutional standpoint. Anyone is free to republish and/or quote this post without prior consent. Please provide a full reference, clearly stating Bruegel and the relevant author as the source, and include a prominent hyperlink to the original post.

View comments
Read article More on this topic

Blog Post

Zsolt Darvas
DSC_0798
dsc_1000

The UK’s Brexit bill: what are the possible liabilities?

The EU-UK financial settlement will be a complex part of the Brexit negotiations. Here the authors estimate that at end-2018 the EU will have outstanding commitments and liabilities totalling €724bn. Most of these relate to spending after the UK’s likely departure date, but are tied to commitments made during the UK’s EU membership.

By: Zsolt Darvas, Konstantinos Efstathiou and Inês Goncalves Raposo Topic: European Macroeconomics & Governance Date: March 30, 2017
Read article More on this topic

Blog Post

Zsolt Darvas
DSC_0798
dsc_1000

Brexit bill negotiators must answer these 12 questions

Is Brexit a divorce, or is the UK leaving a club? This is the first question to answer as negotatiors discuss the key aspects of the EU-UK financial settlement. The authors present various scenarios, and find that the UK could be expected to pay between €25.4 billion and €65.1 billion. But the final cost can only be calculated after extensive political negotiations.

By: Zsolt Darvas, Konstantinos Efstathiou and Inês Goncalves Raposo Topic: European Macroeconomics & Governance Date: March 30, 2017
Read article Download PDF More on this topic

Working Paper

WP_2017_03 cover

Divorce settlement or leaving the club? A breakdown of the Brexit bill

To bring transparency to the debate on the Brexit bill and to foster a quick agreement, the authors of this Working Paper make a comprehensive attempt to quantify the various assets and liabilities that might factor in the financial settlement.

By: Zsolt Darvas, Konstantinos Efstathiou and Inês Goncalves Raposo Topic: European Macroeconomics & Governance Date: March 30, 2017
Read article More by this author

Blog Post

Giuseppe Porcaro

29 charts that explain Brexit

From financial services to the creative industry, from trade to migration, this selection of charts maps out the troubled waters of Brexit, and provides a compass through blogs and publications Bruegel scholars have written on the topic.

By: Giuseppe Porcaro Topic: European Macroeconomics & Governance, Finance & Financial Regulation Date: March 28, 2017
Read article More by this author

Parliamentary Testimony

House of Lords

Brexit: EU budget

On 25 January 2017 Zsolt Darvas appeared as a witness at the House of Lords Select Committee on the European Union, Financial Affairs Sub-Committee.

By: Zsolt Darvas Topic: European Macroeconomics & Governance, House of Lords, Testimonies Date: March 7, 2017
Read article More on this topic

Blog Post

Schoenmaker pic
Nicolas Véron

Brexit should drive integration of EU capital markets

Brexit offers EU-27 countries a chance to take some of London’s financial services activity. But there is also a risk of market fragmentation, which could lead to less effective supervision and higher borrowing costs. To get the most out of Brexit, the EU financial sector needs a beefed up ESMA.

By: Dirk Schoenmaker and Nicolas Véron Topic: Finance & Financial Regulation Date: February 24, 2017
Read article More on this topic

Blog Post

unnamed
Simone Tagliapietra

Brexit goes nuclear: The consequences of leaving Euratom

The UK Government has confirmed that it will withdraw from Euratom. But what does Euratom actually do? And what will happen when the UK leaves? The authors find major risks, potential costs and open questions.

By: Enrico Nano and Simone Tagliapietra Topic: Energy & Climate Date: February 21, 2017
Read article More on this topic

Blog Post

Zsolt Darvas
DSC_0798
dsc_1000

The Brexit bill: uncertainties in the estimate of EU pension and sickness insurance liabilities

Pension and sickness insurance liabilities for EU staff could be an especially contentious part of negotiations on an EU-UK financial settlement: the “Brexit bill”. This post looks behind the calculation of the alleged cost of pension benefits and concludes that it may be less than half of what it seems.

By: Zsolt Darvas, Konstantinos Efstathiou and Inês Goncalves Raposo Topic: European Macroeconomics & Governance Date: February 17, 2017
Read article More on this topic

Blog Post

Zsolt Darvas
DSC_0798
dsc_1000

The UK’s Brexit bill: could EU assets partially offset liabilities?

The ‘Brexit bill’ is likely to be one of the most contentious aspects of the upcoming negotiations. But estimates so far focus largely on the EU costs and liabilities that the UK will have to buy its way out of. What about the EU’s assets? The UK will surely get a share of those, and they could total €153.7bn.

By: Zsolt Darvas, Konstantinos Efstathiou and Inês Goncalves Raposo Topic: European Macroeconomics & Governance Date: February 14, 2017
Read article More on this topic

Blog Post

MariaDemertzis1 bw
unnamed

The impact of Brexit on UK tertiary education and R&D

In this blog post, we look at the impact of Brexit on UK’s education and research and development sectors in terms of students and staff, as well as funding.

By: Maria Demertzis and Enrico Nano Topic: European Macroeconomics & Governance Date: February 14, 2017
Read article Download PDF More on this topic

Policy Contribution

PC 17 04

Brexit and the European financial system

Brexit will lead to a partial migration of financial firms from London to the EU27. This Policy Contribution provides a comparison between London and four major cities that will host most of the new EU27 wholesale market: Frankfurt, Paris, Dublin and Amsterdam. It gives a detailed picture of the wholesale markets, the largest players in these markets and the underlying clearing infrastructure. It also provides data on professional services and innovation.

By: Uuriintuya Batsaikhan, Robert Kalcik and Dirk Schoenmaker Topic: Finance & Financial Regulation Date: February 9, 2017
Read article More on this topic More by this author

Blog Post

Zsolt Darvas

Questionable immigration claims in the Brexit white paper

The UK government's white paper on Brexit suggested that the EU's "free movement of people" has made it impossible to control immigration. This seems to rest on an assumption that EU citizens can "move and reside freely" in any member state. Zsolt Darvas finds these arguments problematic, and points out that it is difficult to infer public opinion about immigration from the referendum result.

By: Zsolt Darvas Topic: European Macroeconomics & Governance Date: February 8, 2017
Load more posts