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A selection of my favourites – June

Category : Data Visualisation

A selection of my favourites – June

 

Sun’s out and so is a new batch of excellent visualisation pieces! This month I have focused on relationships (of data, nothing to do with Mr. Darcy) and the glamorous Cannes Film Festival. So sit back, derive insight and enjoy.

Game of Thrones

Let us start off this month with what is one of my favourite conversational topics – Game of Thrones. Beware, for all of you behind the rest of the world – spoilers alert!

Twitter’s own Krist Wongsuphasawat recently scraped Twitter for the hashtag #GameOfThrones and explored what was tweeted about. This resulted in an interactive network chart with associated sentiment (figure 1).

                                                                                                 

Figure 1 – Game of Thrones

You can even click on the characters to see historical information.

This is a great visualisation for noticing casual relationship, sentiment and character popularity which are all highly important to the show’s many fan theories. In figure 1 however, the focus appears to be on both incredible sadness (hold the door......) and a slightly comedic romance (how can it not be, when you try to flirtatiously eat a chicken leg).

Eurovision

This year’s Eurovision was interesting with an intense final points round. But just how much did the jury and general public agree? Jamie Fry put together the data and published the following relational diagram (figure 2):

                                                                                       

Figure 2 - Eurovision

And although we could talk for hours about the Russia / Ukraine result, what is most interesting is our new “neighbours” from the south – Australia who had a very jury pleasing performance. Poland, on the other hand, appealed more to the general public whilst countries such as Lithuania, Azerbaijan, Cyprus and Hungary united the points givers.

 

 Sharks and humans

National Geographic always provides excellent photographic evidence but this month realised a visualisation showing the approximate size difference between sharks and humans (figure 3).

                                                                                   

Figure 3 - Sharks and humans

 Here I have chosen to screenshot the not-so-appropriately-named Angel Shark, mostly because all the other comparisons were just a little too scary (for the daredevils out there: scroll to the very last shark). The reason why I am including this is because it very clearly communicates data that could otherwise be difficult to relate to, and therefore demonstrates why it is useful to include real comparable data.

Global transportation

Lastly, this month on the topic of relationships we have a proper network diagram of commercial air traffic (figure 4).

                                                                                           

Figure 4 - Air traffic network

Marting Grandjean pulled together publicly available data from 3275 airports. We can very easily identify distinct continental groups, the interrelation within them but also how they are all connected (look at North America and Europe for example). 

Cannes film festival

This month we finish off with the social event of the year (I’m not sure how that is, I did not attend this year) – the Cannes Film Festival. It is only natural to turn to Twitter to see who was most talked about and which movies were mentioned the most. Prophesee analysed over 1 million conversations to find out the answers for us. Let us first have a look at the overall trend (figure 5):

Figure 5 - Cannes film festival

More interestingly, we know that Cannes is more about a Battle Of The Dresses than anything else and the following infographic from the blog provides us that all important winner (figure 6):

Figure 6 - Leading ladies

About the author

Mina Midtgarden
Mina Midtgarden
My aim as an Analytics Consultant is to help clients drive insight from data in order to improve decision making, looking at both unstructured and structured sources. I have experience in business modelling, predictive analytics, text and sentiment analysis and an appetite for outstanding data visualisation.

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