• Login
    View Item 
    •   Mak UD Home
    • College of Computing and Information Sciences (CoCIS)
    • School of Computing and Informatics Technology (CIT)
    • School of Computing and Informatics Technology Collection
    • View Item
    •   Mak UD Home
    • College of Computing and Information Sciences (CoCIS)
    • School of Computing and Informatics Technology (CIT)
    • School of Computing and Informatics Technology Collection
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Social media posts classification system

    Thumbnail
    View/Open
    Undergraduate dissertation (2.416Mb)
    Date
    2019-05
    Author
    Atwine, Nickson
    Mugabo, Amuza
    Turyahiirwa, Happiness
    Mulindwa, Henry
    Metadata
    Show full item record
    Abstract
    This report demonstrates the production of a sentiment analysis system, with the following main objectives set: 1. Implement a machine learning algorithm to perform sentiment analysis. 2. Understand and implement natural language processing technique. 3. Achieve a classification accuracy of over 75%. 4. Build a graphical user interface to enhance the interaction with the users of the system as well as manage users of the system and also for visualization purpose. In order to produce the software artefacts presented in the report, computer science knowledge, as well as machine learning and natural language processing techniques were employed. Consequently, the concepts and techniques, which contributed to the development of the project, such as the Naive Bayes algorithm, logistic regression, are explained. Furthermore, a high-level view and a low-level view of the system produced are detailed in subsequent chapters. The quality is assessed in the Achievements section, where a performance benchmark and other evaluation techniques are employed.
    URI
    http://hdl.handle.net/20.500.12281/8467
    Collections
    • School of Computing and Informatics Technology Collection

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of Mak UDCommunities & CollectionsTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy TypeThis CollectionTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV