A Natural Language Question Answering System for Exploring Online Conversations

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dc.contributor.advisorPrince, Enamul Hoque
dc.contributor.authorSiddiqui, Nadia Ashfaq
dc.date.accessioned2021-03-08T17:30:20Z
dc.date.available2021-03-08T17:30:20Z
dc.date.copyright2020-11
dc.date.issued2021-03-08
dc.date.updated2021-03-08T17:30:20Z
dc.degree.disciplineInformation Systems and Technology
dc.degree.levelMaster's
dc.degree.nameMA - Master of Arts
dc.description.abstractThe proliferation of social media has resulted in the exponential growth of on- line conversations. Due to the volume and complexity of conversations, it is often extremely difficult to gain insights from such conversations. This dissertation hy-pothesizes that synergetic integration of natural language processing with informa-tion visualization techniques can help users to better fulfill their information needs. More specifically, we developed a question-answering method that allows the user to ask questions about a conversation and then automatically answers the question by highlighting results in a visual interface. The visual interface, named ConVisQA, was developed by extending ConVis which visually summarizes a conversation by providing an overview of topics and sentiment information. We demonstrate the effectiveness of our approach through a user study with blog readers. The dis-sertation concludes with a user study comparing our interface with a traditional interface for blog reading as well as considerations for future work.
dc.identifier.urihttp://hdl.handle.net/10315/38243
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subject.keywordsNatural Language Processing
dc.subject.keywordsInfoViz
dc.subject.keywordsQuestion Answering
dc.titleA Natural Language Question Answering System for Exploring Online Conversations
dc.typeElectronic Thesis or Dissertation

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