Sentiment and topic classification of messages on Twitter: and using the results to interact with Twitter users
Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
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.
UPTEC F, ISSN 1401-5757 ; 16012
Computer and Information Science Engineering and Technology
IdentifiersURN: urn:nbn:se:uu:diva-294364OAI: oai:DiVA.org:uu-294364DiVA: diva2:929542
Master Programme in Engineering Physics
Nyberg, Tomas, ForskareSumpter, David, Professor