Opinionist

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dc.contributor.author Waheed, Sadia Reg # 31243
dc.contributor.author Yaseen, Saira Reg # 31245
dc.contributor.author Abid, Sumayya Reg # 31253
dc.date.accessioned 2017-06-19T08:42:27Z
dc.date.available 2017-06-19T08:42:27Z
dc.date.issued 2016-05
dc.identifier.uri http://hdl.handle.net/123456789/1826
dc.description Supervised by Engr. Bushra Fazal en_US
dc.description.abstract The world of technology is developing rapidly and people are adopting to social media fast. To this day twitter is one of the most popular social network. Personal opinions regarding “everything” is shared on the social media. This data is very useful for gathering public opinion. Opinionist provides a web based platform for user to fetch tweets on a desired topic and displays the result in the form of graphical notations. This makes it easier for the user to determine whether the public opinion is positive or negative about the particular topic. The Opinionist uses three sentiment analysis techniques namely Naive Bayes Algorithm, Lexicon Bayes approach and Support Vector Machine Algorithm. Using the result of the three algorithms and produces an average and displays it along with the results produced by the three algorithm. Use of averaging reduces extreme values giving a more general and realistic value. en_US
dc.language.iso en_US en_US
dc.publisher Bahria University Karachi Campus en_US
dc.subject Stop-words, Opinion Mining, Sentiment analysis, Lexicon, Naive Bayes, Support Vector Machine. en_US
dc.title Opinionist en_US
dc.type Thesis en_US


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