Researchers came up with a ranking model for the characters based on how likely they are to die.
"I am probably not alone in wondering which of my favourite characters are going to meet their ends, and which will live on to the next season," said Milan Janosov, PhD candidate at Central European University in Hungary.
The model finds the probabilities of each living well- known character passing away. Janosov ranked the characters in increasing order of survival according to the final prediction model.
Grey Worm, commander of Daenerys's Unsullied army, ranks third on the list of characters most likely to die next.
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Tyrion Lannister and Jon Snow seem to be relatively safe.
Arya Stark and the Hound, already so close to death many times before, are both in dangerous positions.
Cersei, currently sitting on the Iron Throne, and Petyr Baelish, who is doing his best to get there, seem to be in a much better position.
"Game of Thrones is a complex world in which social position and true friends seem to be quite important, so I quantified each character's social interaction patterns using the tools of network science," Janosov.
"I then predict their fate using machine learning methods," he said.
Researchers used the show's subtitles, collected in dialogue format. They constructed the aggregated network of the realm's social system.
In this network each node represents a character of the story, and the weight of the link between each pair of characters indicates the strength of their social interaction.
This means that everyone who appeared once together in the same scene has a tie with strength of one, and within a scene everyone is connected with everyone.
In other words, scenes are complete graphs, or cliques, increasing the tie strength between all pairs of people present by one.
By calculating these scene-level complete networks and then aggregating them, researchers arrived to the global social network of Westeros, which has almost 400 nodes and more than 3,000 edges.
Using machine learning and data from characters that have already died, researchers predicted who is going to die in the near future.
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