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Troll detection: A comparative study in detecting troll farms on Twitter using cluster analysis
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Trolldetektion : En jämförande studie i att upptäcka trollfarmar på Twitter medhjälp av klusteralgoritmer (Swedish)
Abstract [en]

The purpose of this research is to test whether clustering algorithmscan be used to detect troll farms in social networks. Troll farms are profes-sional organizations that spread disinformation online via fake personas.The research involves a comparative study of two different clustering algo-rithms and a dataset of Twitter users and posts that includes a fabricatedtroll farm. By comparing the results and the implementations of the K-means as well as the DBSCAN algorithm we have concluded that clusteranalysis can be used to detect troll farms and that DBSCAN is bettersuited for this particular problem compared to K-means.

Abstract [sv]

Målet med denna rapport är att testa om klusteringalgoritmer kananvändas för att identifiera trollfarmer på sociala medier. Trollfarmer ärprofessionella organisationer som sprider desinformation online med hjälpav falska identiteter. Denna rapport är en jämförande studie med två olikaklusteringalgoritmer och en datamängd av Twitteranvändare och tweetssom inkluderar en fabrikerad trollfarm. Genom att jämföra resultaten ochimplementationerna av algoritmerna K-means och DBSCAN får vi framslutsatsen att klusteralgoritmer kan användas för att identifiera trollfar-mar och att DBSCAN är bättre lämpad för detta problem till skillnadfrån K-means.

Place, publisher, year, edition, pages
2016.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-186406OAI: oai:DiVA.org:kth-186406DiVA: diva2:927209
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Available from: 2016-05-12 Created: 2016-05-11 Last updated: 2016-05-12Bibliographically approved

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CiteExportLink to record
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