A little over six weeks ago, the political internet tool Tweetminster was predicting that Labour was set to win the general election.

It was a prediction based on its analysis of activity by and about political candidates in most UK constituencies - 433 out of 650. To be fair, Tweetminster regularly revised its predictions throughout the campaign and as it gathered more data from Twitter, ultimately processing more than 2m tweets by election day, it became more and more accurate.

So how did Tweetminster do on the final result?

The results

The study found the results proved as accurate as traditional opinion polls, with a definite correlation between the visibility of a candidate on twitter and their performance at the polls.

Predictions for national results were more accurate (90.5%) than predictions for regional results (87.5%), which in turn were more accurate than results for individual candidates (69%); this was down to the volume of tweets at each level, so national vote share predictions were more accurate because they were based on more data.

National share of the vote

Vote share fluctuated by a few percentage points over the six weeks but the final Tweetminster prediction was:

Conservatives 35%

Labour 30%

Liberal Democrats 27%

Others 8%

The actual results were:

Conservatives 37%

Labour 30%

Liberal Democrats 24%

Others 10%

The results were less accurate than ICM but as accurate as Ipsos Mori and more accurate than YouGov, ComRes, Opinium and Angus Reid. It was a YouGov/Sun poll on the night of the first election TV debate that caused disbelief on Twitter; the prediction that David Cameron had won that round was very different to public sentiment.

Tweetminster results had an average error margin of 1.75% - compared to 2.25% for YouGov.

Regional party results

Of eight predictions, Tweetminster was right on all but one, which was that the Tories would gain seats in Scotland. They predicted the SNO would not gain seats in Scotland, which it didn't, that Labour would perform better than predicted in London - the Labour to Tory swing was 2.5% compared to 6.1% nationally - and the Conservatives did perform well in the East Midlands, where they gained 12 seats.

Constituency results

Though this data proved less reliable in terms of predicting the winner, 69% of the time in seats where all major parties had a candidate on Twitter, it was the candidate most mentioned on Twitter that won.

The Green Party's win with Caroline Lucas in Brighton Pavilion was predicted by Twitter's 'buzz' but disproportionate media coverage of Esther Rantzen in Luton skewed the results there and she did not win the seat.

Tweetminster says these results prove "the wisdom of the clouds" and supports the case that "measurements made through data mining in social media channels can be as reliable as traditional opinion polling techniques" when the sample size is sufficiently large".

So it seems there is a point to all this Twittering, after all: "Twitter users... are the insightful and indicators of public opinion and behaviour."