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Sentiment and topic classification of messages on Twitter: and using the results to interact with Twitter users
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
2016 (English)Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

We classify messages posted to social media network Twitter based on the sentiment and topic of the messages. We use the results of the classification to sometimes generate responses that are sent to the original user and their network on Twitter using natural language processing. A network of users who post science related content is used as the sources of data. The classifications of the dataset show worse results than others have achieved for sentiment analysis of content on Twitter, possibly due to the data sets that were used. 

Place, publisher, year, edition, pages
2016. , 18 p.
Series
UPTEC F, ISSN 1401-5757 ; 16012
National Category
Computer and Information Science Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-294364OAI: oai:DiVA.org:uu-294364DiVA: diva2:929542
Educational program
Master Programme in Engineering Physics
Supervisors
Examiners
Available from: 2016-05-27 Created: 2016-05-19 Last updated: 2016-05-27Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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