Computer scientists from The University of Warwick are using Twitter to predict the UK General Election result and claim their model could provide most accurate forecasts yet.
The academics have created a data model in collaboration with the Department of Journalism at City University London and the Information Technologies Institute (ITI-CERTH) in Greece.
Together, the team is using an algorithm which harvests political tweets, aggregates various features about every party and then injects this information into conventional polling reports, producing a daily prediction of voting share.
With the outcome of the General Election in terms of seats more uncertain than ever, this approach will provide crucial insights into how public opinion is developing and what factors might be influencing any changes in support.
Early results of the system have already tracked the surge in support for the SNP and the fluctuating fortunes of UKIP.
Warwick researcher Adam Tsakalidis said: "We are trying to define and extract meaningful features out of the noisy, user-generated content published in Twitter.
"This includes the number of users mentioning a political party and (those) who have expressed a negative opinion about this party on a certain day.
"We then put all this information into our forecasting model, along with the parties' share of the vote as measured by opinion polls.
"Predicting elections using social media data has been tried in the past, with varying results. We have evidence from our previous work that our approach is very effective."
Mr Tsakalidis tested the model in the Greek election in January, achieving better results than all 31 most recent polls leading to the election, as well as the three exit polls that were announced once the ballots closed.
The model being used was successfully applied in three different countries in the EU 2014 elections, as part of the SocialSensor research project.