Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1363
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dc.contributor.authorCooray, T.-
dc.contributor.authorPerera, G.-
dc.contributor.authorChandrasena, D.-
dc.contributor.authorAlosius, J.-
dc.contributor.authorKugathasan, A.-
dc.date.accessioned2022-02-23T05:25:33Z-
dc.date.available2022-02-23T05:25:33Z-
dc.date.issued2020-12-10-
dc.identifier.isbn978-1-7281-8412-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1363-
dc.descriptionPrint on Demand(PoD) ISBN:978-1-7281-8413-5en_US
dc.description.abstractAspect-based sentiment analysis (ABSA) is used in different fields for analyzing customer reviews to project an overall customer opinion on certain products. With the expansion of the internet, people are provided with an inexpensive and time-saving method to express their opinion to a larger audience, while various industries are handed with the opportunity to gather free information from it to obtain market value. The implementation of machine learning methods for the evaluation of aspects related to movies and television series has not been commenced, and it could be a new development for the industry. This study focuses on conducting an ABSA on a movie or a television series based on genre, story as well as cast and crew aspects. The data collected from social media through web scraping is processed to produce adequate results to get a broad understanding on how the popularity of the movie or the television series related to above mentioned aspects. Then, each aspect is further analyzed to gather precise information belonging to each aspect. The accuracy of the results of the proposed system has been achieved over 79%. The results proved that the solution is highly successful than the former works with high business value.en_US
dc.language.isoenen_US
dc.publisher2020 2nd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.relation.ispartofseriesVol.1;-
dc.subjectAspect Based Sentiment Analysisen_US
dc.subjectNatural Language Processingen_US
dc.subjectArtificial Neural Networken_US
dc.subjectSupport Vector Machineen_US
dc.subjectBitmask Bidirectional Long Short-Term Memoryen_US
dc.titleAspect Based Sentiment Analysis for Evaluating Movies and TV series Publisher: IEEE Cite This PDFen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC51239.2020.9357129en_US
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
Department of Computer Science and Software Engineering-Scopes
Department of Computer Science and Software Engineering-Scopes

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