Predicting the General Election result: what data can and can't tell us
The outcome of the May 7 vote is anticipated to be the hardest election to predict in recent memory.
For the first time ever, it’s conceivable that the joint vote share of the two main parties might be under 60 per cent.
In 2012, Nate Silver, author of the exceptional data blog FiveThirtyEight, famously used the same analytic models he applied to sports betting to predict the US presidential election result.
Crucially, each contest had a relative likelihood of success, and mounting those probabilities up across the whole election returned a remarkably accurate result.
The UK political scene, however, has become a little more complex. No longer a simple red vs. blue contest, parties historically considered to be on the fringes have taken the fight to the incumbents.
The Liberal Democrats (although in fairness an incumbent themselves), Scottish National Party (SNP), United Kingdom Independence Party (UKIP), Green and Plaid Cymru (Party of Wales) have divided voters and complicated our forecasting models.
The UK system dictates that the party with the most seats wins, but each of the 650 seats has to be fought for one by one. The importance of a majority in each location or constituency adds another layer of intricacy to our calculation.
Historically, it’s been possible to predict seat outcomes by factoring in the change in the opinion poll as compared to the last election.
For example, if one party won the seat with 40 per cent of the votes, and their opinion poll rating has dropped by 10 per cent, you could reduce that 40 per cent by 10 per cent, giving 36 per cent, meaning they may lose the seat.
Now that we’re looking at a six party race, split across 650 seats, a more intricate model is required. In a bid to show what Parliament would look like based on the latest polls, The Guardian has produced an interesting projection methodology.
Whilst the model has become more complex, the good news is that there are a number of data points that we can add into our calculations.
Opinion polls are the most traditional source of up-to-date information on which way the public is leaning. However, polls can occasionally mislead us as they did in 1992, where the final polls predicted a 1.4 per cent Labour lead but the Conservatives won by 7.6 per cent.
Betting markets are often touted as a reliable source, with Professor Leighton Vaughan Williams, director of the Political Forecasting Unit at Nottingham Business School, claiming they are more accurate than the polls.
The emergence and mining of social media data can track party and voter sentiment. For the first time in the UK, apps are available which enable the general public to follow the trends and gain insight into the mood around the main parties.
Social media, however, tends to be a fairly biased sample and can mislead. When it came to the referendum on the Alternative Voting system in 2011, social media suggested a big win for AV. The status quo won out.
To make meaningful predictions about the result in constituencies, or indeed nationally, you need the capability to analyse a much wider pool of data.
Search engine data sourced remarkably accurate results for the referendum on Scottish Independence. However, given certain party leaders’ penchant for headline grabbing statements, search volumes could be more of an indicator of celebrity than of potential success.
The views and opinions expressed in this article are those of the author(s) and do not necessarily reflect the official policy or position of The Information Daily, its parent company or any associated businesses.
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