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Troll Detection: A study of source usage between clusters of Twitter tweets todetect Internet trolls
KTH, School of Computer Science and Communication (CSC).
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Trolldetektion : En undersökning av källanvändning mellan kluster av Twitter tweets för att detektera Internettroll (Swedish)
Abstract [en]

The purpose of this study was to examine whether it is possible to detect possibly malicioustweets posted by so-called trolls by inspecting the usage of sources such as url links,hashtags, user mentions and other media between clusters of tweets. This was done byutilizing the latent dirichlet allocation algorithm to find and assign topics to every tweet,clustering the tweets through their topics with the k-means algorithm. The resulting clusterswas iterated through and data fetch and summarized to examine any difference between theclusters. The results suggest that this method for finding trolls is, in combination with alexical study of the tweets text, plausible.

Abstract [sv]

Syftet bakom denna studie var undersöka ifall det är möjligt att detektera sannolikt illvilligatweets postad av så kallade troll genom att inspektera användandet av källor såsomurl-länkar, hashtaggar, omnämnande av användare och annan media mellan olika kluster avtweets. Detta utfördes med hjälp av latent dirichlet allocation algoritmen för att finna ochtilldela ämnen till varje tweet, där tweeten klustrades på deras ämnestilldelning med hjälpk-means metoden. De resulterande klustrena itererades igenom och data från tweetenhämtades och summerades för att undersöka skillnader mellan klustrena. Resultatenantyder att denna metod tillsammans med en analys av tweetens text är möjligtvis lämpligför att detektera troll.

Place, publisher, year, edition, pages
2017. , p. 61
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-209436OAI: oai:DiVA.org:kth-209436DiVA, id: diva2:1112015
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2017-06-19 Created: 2017-06-19 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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