Troll detection with sentiment analysis and nearest neighbour search

Detta är en Kandidat-uppsats från KTH/Skolan för datavetenskap och kommunikation (CSC)

Författare: Oskar Casselryd; Filip Jansson; [2017]

Nyckelord: ;

Sammanfattning: Internet trolls are gaining more influence in society due to the rapidgrowth of social media. A troll farm is a group of Internet trolls that get paid to spread certain opinions or information online. Identifying a troll farm can be difficult, since the trolls try to stay hidden. This study examines if it is possible to identify troll farms on Twitter by conducting a sentiment analysis on user tweets and modeling it as a nearest neighbor problem. The experiment was done with 4 simulated trolls and 150 normal twitter users. The users were modelled into datapoints based on the sentiment, frequency and time of their tweets. The result of the nearest neighbor search could not show a clear link between the trolls as their behaviour was not similar enough.

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