THE A12 is the most rage-inducing road in the whole of the UK, according to new analysis of people's Tweets.

The team at FleetLogging.com analysed nearly 60,000 traffic-related tweets and ran them through a sentiment and stress analysis tool called TensiStrength.

The resulting study revealed the roads, cities and states which cause the most stress in Britain.

According to the analysis the A12, which connects Essex with London and Suffolk, is the most stress inducing road in the UK.

FleetLogging found almost 93 per cent of Tweets about the A12 were from annoyed residents.

A12 traffic from Stadium bridge looking towards Ardleigh Interchange.

 

This was the highest percentage of any of the roads analysed in Britain.

Second place was the A1, where 91.6 per cent of Tweets were annoyed.

But what do you think?

Is the A12 the most rage-inducing road in Essex? 

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Stressful traffic. Picture: FleetLogging.com

Picture: FleetLogging.com

The analysis also found one part of Essex ranked in the top ten by the percentage of rage-filled Tweets.

Chelmsford came in seventh position out of places in the UK.

Stressful traffic. Picture: FleetLogging.com

Picture: FleetLogging.com

More than 62 per cent of traffic-related tweets made in the city were from stressed drivers.

The place with the most stressed drivers in the UK was found to be Telford in the West Midlands, where 83.3 per cent of traffic tweets were stressed.

Perhaps surprisingly, of the 48 cities where data was analysed, Southend came out as the least stressed.

Just 10.9 per cent of traffic-tweets in the town were from road-raging residents.

How did the study work?

RTC and traffic delays Southbound on A12 at Eight Ash Green turn off..
 

Using Twitter API, FleetLogging collected 57,282 tweets which featured the keyword "traffic" written in English and posted in UK.

The team removed tweets from traffic update accounts.

Then the data team used a sentiment and stress analysis tool called TensiStrength to classify every tweet as stressed or not.

To detect the location of each tweet, the team referred to the post coordinates or the location mentioned in their profile.

To get the breakdown by roads, they first took the lists of most congested roads from a number of different sources.

They then extracted tweets which contained the names of those roads.

You can view the full research here.