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What we talk about when we talk about winners: Using clustering of Twitter topics as a basis for election prediction
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Vad pratar vi om när vi pratar om vinnare? : En studie i det potentiella användandet av clustering av twitterämnen för att förutsäga valresultat (Swedish)
Abstract [en]

Social media has over the years partly become a platform to express opinions and discuss current events. Within the field of Computer Science, Twitter has been used both as the basis for political analysis - for example using sentiment analysis to predict election results - and within the field of cluster analysis, where the question of how to best design and use an algorithm to extract topics from tweets has been studied. The ClusTop algorithm is specifically designed to cluster tweets based on topics. This paper aims to explore whether it is possible to (a) use an implementation of the ClusTop algorithm to identify topics connected to tweets about Trump and Clinton just before the American 2016 election, and (b) distinguish between the topics used in connection with a specific candidate in states where they won versus states where they lost the election. The problem is approached through the method of a controlled experiment where the data collected from Twitter is divided into groups and run through the ClusTop algorithm. The topics are then compared to draw tentative conclusions about their validity as a basis for election prediction. The study finds that it is indeed possible to adapt the ClusTop algorithm to use with tweets and geolocation to identify different topics, thus confirming the usefulness of the algorithm. In addition to this, the study confirms that manually examining the words used within the topics makes it possible to see differences between them. The work thereby places itself in the tradition of exploring how Twitter can be used for election prediction by being one of the first studies to look at clustering as a way of approaching the problem.

Place, publisher, year, edition, pages
2019. , p. 55
Keywords [en]
Twitter, clustering, cluster analysis, ClusTop, election prediction, election results, American 2016 election
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-84789OAI: oai:DiVA.org:lnu-84789DiVA, id: diva2:1321834
Subject / course
Computer Science
Educational program
Datavetenskap, kandidatprogram, 60 hp
Supervisors
Examiners
Available from: 2019-06-10 Created: 2019-06-10 Last updated: 2019-06-10Bibliographically approved

Open Access in DiVA

What We Talk About When We Talk About Winners - Bachelor's Thesis(17038 kB)44 downloads
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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More styles
Language
  • de-DE
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  • nn-NB
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  • Other locale
More languages
Output format
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