Opinion Detection, Sentiment Analysis and User Attribute Detection from Online Text Data
نام عام مواد
[Thesis]
نام نخستين پديدآور
Kasturi Bhattacharjee
نام ساير پديدآوران
Petzold, Linda
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
University of California, Santa Barbara
تاریخ نشرو بخش و غیره
2016
مشخصات ظاهری
نام خاص و کميت اثر
142
يادداشت کلی
متن يادداشت
Committee members: Friedkin, Noah; Yan, Xifeng
یادداشتهای مربوط به نشر، بخش و غیره
متن يادداشت
Place of publication: United States, Ann Arbor; ISBN=978-1-369-34001-3
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
Ph.D.
نظم درجات
Computer Science
کسي که مدرک را اعطا کرده
University of California, Santa Barbara
امتياز متن
2016
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
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.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Computer science
اصطلاحهای موضوعی کنترل نشده
اصطلاح موضوعی
Applied sciences;Data mining;Natural language processing;Online social network analysis;Opinion mining;Sentiment analysis;User attribute detection
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )