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dc.contributor.advisorWilliams, Daviden
dc.contributor.authorSinha, Ashish
dc.date.accessioned2020-02-13T15:23:59Z
dc.date.available2020-02-13T15:23:59Z
dc.date.issued2019
dc.identifier.citationSinha, A. (2019). Twitter sentiment analysis with deep learning technique for self-driving cars. Masters Thesis, Dublin Business School.en
dc.identifier.urihttps://esource.dbs.ie/handle/10788/3978
dc.description.abstractSocial media is an evolving platform for influencers, decision-makers and the common people to express their opinions. Social listening has changed the approach of brands when it comes to promoting and determining the market value of their product. Sentiment analysis has become a vital tool to understand the flow of the market via social media. Twitter is one of the leading platforms in this context. With its massive user base and significant amount of data, it has proved to be a goldmine for such a task. In this paper, we will explore and study how deep learning techniques impact the classification and gain insight on the sentiment of Self-Driving Cars. It combines word embedding and deep neural network to accomplish the task. The outcome is a multi-class sentiment classification. Based on the result, we can determine that the model achieved an accuracy of 70% and efficiently answered our research questions.en
dc.language.isoenen
dc.publisherDublin Business Schoolen
dc.rightsItems in eSource are protected by copyright. Previously published items are made available in accordance with the copyright policy of the publisher/copyright holder.en
dc.rights.urihttp://esource.dbs.ie/copyrighten
dc.subjectDeep Learningen
dc.subjectTwitteren
dc.subjectAutomated vehiclesen
dc.titleTwitter sentiment analysis with deep learning technique for self-driving carsen
dc.typeThesisen
dc.rights.holderCopyright: The authoren
dc.type.degreenameMSc in Data Analyticsen
dc.type.degreenameMSc


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