So what does the Twitter chatter around the hit TV show Game of Thrones look like? Well I decided to try and find out.

I set up a small experiment where I collected tweets about the hit TV series over the last three weeks of the recently concluded Season 04. Then I added some D3.js visualization magic to the data and presto!!! I had some impressive insights into the twitter chatter around the series.
I managed to collect about 2.72 million tweets. A quick analysis on the numbers showed that about 114K unique users were responsible for those tweets sharing about 102K links. About 36% of those tweets were retweets.

Timeline of Tweets

Timeline of Tweets

An analysis of the timeline showed regular peaks around episode air dates with the episode “The Mountain and The Viper” garnering most reactions on Twitter.

Tweet volume by Day of Week and Hour

Tweet volume by Day of Week and Hour

An analysis of the hour vs. the day, on which tweets were sent out, shows that the busiest hours for tweeting were on Sunday night. After that, the next slot of busy hours occurred on Monday evening. This ties in nicely with the fact that those two slots are approximately just after the time when Game of Thrones airs in the USA and UK respectively. The twitter traffic kind of peters out over the rest of the week, and picks up again on Sunday afternoon, in anticipation of the next episode.

So what did twitter users say about the show? Apparently quite a lot as the word cloud below shows.

Word Cloud of Tweets

Word Cloud of Tweets

Some words that stand out include “Season”, “Finale”, “watch” and words like “Oh”, “Killing”, “Shocking”, “OMG”, “Sad” that kind of sum up the jolt that fans got in the episode titled “The Mountain and The Viper”. The most shared status message was this one from show star, Maisie Williams:

Talk about stars, and you come to the characters on the show, that we have all come to love and hate in equal measure. So, who do the Twitter folk like to tweet about?

Popular Characters

Popular Characters

Well, five characters clearly stand out in the three weeks viz. Oberyn Martell (The Red Viper), Jon Snow, Arya Stark, Gregor Clegane (The Mountain) and everyone’s favourite Tyrion Lannister. But if you look at each character, which episodes are the character’s defining moments? The below visualization attempted to answer that.

Characters by Tweet volume and Day

Characters by Tweet volume and Day

Here I plotted the number of tweets by day for each character, with the size of each circle giving relative tweet volumes for a character. A cursory glance showed some nice insights.
In this season, the final episode very neatly tied up the character story arcs for almost all of the many characters in the show. So most of the characters saw maximum volumes around the day when the last episode aired. However some characters differed from the norm.
For example, Ygritte and Jon Snow, both saw the highest number of mentions in the episode “The Watchers on the Wall”, since that episode almost exclusively focussed on their part of the Game of Thrones universe. Similarly, Oberyn Martell and The Mountain, naturally saw the maximum number of mentions in the episode “The Mountain and The Viper”, which featured their epic showdown.

Countries by Tweet Volume

Countries by Tweet Volume

And where did they tweet from? Apparently the show has universal appeal with tweets recorded from all over the globe, including countries where the show does not air. I wonder now how they managed to watch that ;)
Obviously the show is most popular in the USA and the UK, but I was very surprised to see tweets from places like Greenland, Mongolia, Sudan and even from what seemed like a passing ship !!!

Unfortunately, due to the lack of geo-location data in every tweet, the number of actual tweets that had geo-location data amounted to only about 3-4% of the total number of tweets. Nevertheless, plotting the tweets on a world map resulted in the below graphic.

Tweets by Location

Tweets by Location

For an interactive version of this map and the other graphical analysis, do take a look at the companion micro-site.
In the coming weeks, I’ll be writing about the technology behind all the pretty visualizations and analysis that were detailed in this post. So do watch this blog for more.
Lastly, a big thank you to Mark DiMarco who helped me with his DataMaps library. Mark, without the quick response to my queries I would have struggled for quite a bit to build out that beautiful “Choropleth” world map that you saw above. Thanks a ton again!!!

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3 Comments

  1. saurabh says:

    very very thorough … nice job!!!

  2. Sumanth Cheedella says:

    Excellent work!!