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" Opinion Detection, Sentiment Analysis and User Attribute Detection from Online Text Data "
Kasturi Bhattacharjee
Petzold, Linda
Document Type
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Latin Dissertation
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Language of Document
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English
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Record Number
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804277
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Doc. No
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TL49102
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Call number
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1853205902; 10191170
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Main Entry
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Makstenieks, Scott T.
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Title & Author
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Opinion Detection, Sentiment Analysis and User Attribute Detection from Online Text Data\ Kasturi BhattacharjeePetzold, Linda
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College
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University of California, Santa Barbara
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Date
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2016
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Degree
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Ph.D.
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field of study
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Computer Science
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student score
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2016
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Page No
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142
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Note
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Committee members: Friedkin, Noah; Yan, Xifeng
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Note
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Place of publication: United States, Ann Arbor; ISBN=978-1-369-34001-3
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Abstract
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With the growing increase in the use of the internet in most parts of the world today, users generate significant amounts of online text on different platforms such as online social networks, product review websites, travel blogs, to name just a few. The variety of content on these platforms has made them an important resource for researchers to gauge user activity, determine their opinions and analyze their behavior, without having to perform monetarily and temporally expensive surveys. Gaining insights into user behavior enables us to better understand their likes and dislikes, which in turn is helpful for economic purposes such as marketing, advertising and recommendations. Further, owing to the fact that online social networks have recently been instrumental in socio-political revolutions such as the Arab Spring, and for awareness-generation campaigns by MoveOn.org and Avaaz.org, analysis of online data can uncover user preferences.
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Subject
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Computer science
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Descriptor
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Applied sciences;Data mining;Natural language processing;Online social network analysis;Opinion mining;Sentiment analysis;User attribute detection
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Added Entry
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Petzold, Linda
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Added Entry
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Computer ScienceUniversity of California, Santa Barbara
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