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Opinion Mining/Sentiment Analysis

dc.contributor.authorZakari, Abdul Shakur
dc.date.accessioned2016-06-07T16:06:24Z
dc.date.available2016-06-07T16:06:24Z
dc.date.issued2013-04-15
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/397
dc.identifier.urihttp://library.aust.edu.ng:8080/xmlui/handle/123456789/397
dc.description.abstractThere has been tremendous growth in the amount of user generated content on the Internet. This is due to rise in social networks and the embrace of web 2.0 or technologies. The Internet is no longer a place for consumption of information only, but a melting point of users interacting on various interests. This project concentrates on a specific type of content – opinionated content. Several review sites exist where users can comment on their experience about a movie, product or service. The review sites allow users to rank their experience of such products or service. The literature will be reviewed in detail. Several techniques for automatically analyzing such opinionated data will be explored. The focus will be on semantic orientation of the text. Semantic orientation is a measure of how far the opinion contained in the text differs from the group of other words surrounding the text. And will be implemented and compared with other similar work.en_US
dc.language.isoenen_US
dc.subjectSentiment Analysisen_US
dc.subjectProf David Amosen_US
dc.subject2013 Computer Scienceen_US
dc.subjectZakari Abdul Shakuren_US
dc.titleOpinion Mining/Sentiment Analysisen_US
dc.typeThesisen_US


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  • Computer Science105

    This collection contains Computer Science Student's Theses from 2009-2022

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