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dc.contributor.authorAbu Salih, Bilal Ahmad Abdal Rahman
dc.contributor.supervisorDr Vidyasagar Potdaren_US

This thesis presents several state-of-the-art approaches constructed for the purpose of (i) studying the trustworthiness of users in Online Social Network platforms, (ii) deriving concealed knowledge from their textual content, and (iii) classifying and predicting the domain knowledge of users and their content. The developed approaches are refined through proof-of-concept experiments, several benchmark comparisons, and appropriate and rigorous evaluation metrics to verify and validate their effectiveness and efficiency, and hence, those of the applied frameworks.

dc.publisherCurtin Universityen_US
dc.titleTrustworthiness in Social Big Data Incorporating Semantic Analysis, Machine Learning and Distributed Data Processingen_US
curtin.departmentSchool of Information Systemsen_US
curtin.accessStatusOpen accessen_US
curtin.facultyBusiness and Lawen_US

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