Caterham F1 becomes #drivenbydata thanks to BIPB
As well as sponsoring Caterham F1 team, we’ve been looking at the vast amount of data created during a Grand Prix. These days we are doing more and more work for our clients to help them make sense of unstructured data as well as structured data. This interest in analysing the unstructured data gave us the idea to see if we could spot trends in tweets related to the Caterham F1 team.
By giving over 6500 words a positive or negative weighting we were able to analyse the overall sentiment of each tweet relating to theCaterham F1 team. We’ve then visualised that using Tableau to show the sentiment leading up to and at different points during the race. There are initial peeks in positive tweets at the start of the race when both Caterham’s get off to a flying start ahead of the Red Bull of four time world champion, Sebastian Vettel, his team mate, Daniel Ricardo and the Lotus of Romain Grosjean.
There is a peek in both positive and negative sentiment when Ferrari’s Fernando Alonso overtook Caterham rookie Will Stevenson around the first set of pit stops and there is a clear negative peek when Caterham’s Kamui Kobayashi had to retire from the race due to a mechanical issue. Projects like this allow is to test new ideas and sharpen our approach when analysing vast amounts of data. This puts us in a unique position to help our clients make sense of the increasing verity and complexity of data they have access to, to make better data driven decisions.