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The rich worlds created in the TV-series “Game of Thrones” (GoT), inspired a computer science class at the Technical University of Munich (TUM) in Germany: As part of their class project the students developed applications that scour the web for data about Game of Thrones, crunch the numbers, and put together a website that will report which characters are most likely to die in the upcoming sixth season of the TV-series.
Shortly before the sixth season of the television series “Games of Thrones” starts, computer science students at the Technical University of Munich have realized a project that answers important questions for fans of the series: Has Jon Snow survived the fifth season? Which character in the series is going to die next?
The students used an array of machine learning algorithms to answer the question that is on many Game of Thrones fans mind: “Who is likelier to die next?” The algorithm, that accurately uncovered 74 percent of the actual character deaths in the show and the books, has many surprises in store, putting some of the characters that were thought to be relatively safe in grave danger.
Based on these predictions, it seems likely that the villainous Ramsey Snow (64 percent predicted likelihood of death) is likelier to outlive his runaway captive and mortal enemy Theon Greyjoy (74 percent predicted likelihood of death). The algorithm also has a very clear answer about the fate of Jon Snow, who was betrayed by his friends in the season five finale.
Machine learning and the Twitter-seismometer
The website https://got.show/ presents the most important data generated by the diverse machine learning tools the students combined. The site also keeps track and analyzes how people on Twitter feel about hundreds of GoT characters.
Beyond these predictions, the students also programmed an interactive map that allows fans the ability to explore the Game of Thrones world and chart the journeys taken by major characters.
Season six of Game of Thrones will premiere in the USA on April 24th. Parallel to the US broadcast it will be available in Germany in the night from April 24 to 25 both in English and German on Sky.
Solving real-life problems with big data
“This project has been a lot of fun for us”, says Dr. Guy Yachdav, who led the class and conceived the project. “In its daily work, our research group focuses on answering complex biological questions using data mining and machine learning algorithms. For this project we used similar techniques, just this time the subject matter was a popular TV show. The epic scale of the worlds created by George R. R. Martin provides an almost endless resource of raw multi-dimensional data. It provided the perfect setting for our class.”
“Data mining and machine learning are the tools which enable digital medicine to benefit from modern biology, for diagnosis, treatment, and prevention of diseases. Turning to such a “real life” challenge created a didactical jewel, winning students for these subjects”, summarizes Burkhardt Rost, Professor for Bioinformatics at the Technical University of Munich. “And the interactive visual maps created in the project might open a new approach to data visualization that we will follow up scientifically.“
http://www.rostlab.org Website of the Chair for Bioinformatics
https://got.show/ GoT-website of the students
http://www.in.tum.de/en.html Website of the Department of Informatics
Machine learning algorithms predict what happens next in the TV-series Game of Thrones
Source: Christian Dallago / TUM
The JavaScript-class at Technical University of Munich
Source: Lothar Richter / TUM
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Machine learning algorithms predict what happens next in the TV-series Game of Thrones
Source: Christian Dallago / TUM
The JavaScript-class at Technical University of Munich
Source: Lothar Richter / TUM
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