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Computer algorithms predict next characters to be eliminated in “Game of Thrones”
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 on the Game of Thrones and crunch the numbers. They then put together a website that reports which characters are most likely to die in the upcoming sixth season of the TV series.
Just ahead of the kickoff for Season 6 of the television series “Games of Thrones,” computer science students at the Technical University of Munich have implemented a project that answers questions preoccupying fans of the series: Has Jon Snow survived Season 5? Who is going to die next?
The students used an array of machine learning algorithms to answer a key question on minds of many Game of Thrones fans: “Which character is most likely to die next?” The algorithm, which accurately predicted 74 percent of character deaths in the show and books, has many surprises in store, placing a number of characters thought to be relatively safe in grave danger.
Based on these predictions there is a good chance that the villainous Ramsey Snow (64 percent likelihood of death) will outlive his runaway captive and mortal enemy Theon Greyjoy (74 percent likelihood of death). The algorithm also gives a very clear answer on the fate of Jon Snow, who was betrayed by his friends in the Season 5 finale.
Machine learning and the Twitter seismometer
The website https://got.show/ presents key data generated by the students’ diverse machine learning tools compilation. The site also tracks and analyzes Twitter user sentiments on hundreds of GoT characters.
Beyond these predictions, the students also programmed an interactive map that allows fans to explore the Game of Thrones world and chart the journeys taken by major characters.
Game of Thrones Season 6 will premiere in USA on April 24th. It will also air in France on April 24th and 25th.
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. Only 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 tools that enable digital medicine to benefit from modern biology for diagnosis, treatment and prevention of disease. Turning to such a ‘real life’ challenge created a didactical jewel, winning students for these subjects,” summarizes Burkhardt Rost, Professor of 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.”
Website of the Chair of Bioinformatics: http://www.rostlab.org
GoT-website of the students: https://got.show/
Website of the Faculty of Informatics: http://www.in.tum.de
Dr. Guy Yachdav
Technical University of Munich (TUM) is one of Europe’s leading research universities, with more than 500 professors, around 10,000 academic and non-academic staff, and 39,000 students. Its focus areas are the engineering sciences, natural sciences, life sciences and medicine, reinforced by schools of management and education. TUM acts as an entrepreneurial university that promotes talents and creates value for society. In that it profits from having strong partners in science and industry. It is represented worldwide with a campus in Singapore as well as offices in Beijing, Brussels, Cairo, Mumbai, San Francisco, and São Paulo. Nobel Prize winners and inventors such as Rudolf Diesel, Carl von Linde, and Rudolf Mößbauer have done research at TUM. In 2006 and 2012 it won recognition as a German “Excellence University.” In international rankings, TUM regularly places among the best universities in Germany. www.tum.de