1. Digital Repository
  2. Science
  3. Symposia & Conferences
  4. Smart Computing and Systems Engineering (SCSE)
  5. Smart Computing and Systems Engineering - 2022 (SCSE 2022)
Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/25429
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWelgamage, V. R.-
dc.contributor.authorSenarathne, U. A. C.-
dc.contributor.authorMadhubhashani, N. H. A. C.-
dc.contributor.authorLiyanage, T. C.-
dc.contributor.authorDinesh Asanka, P. P. G.-
dc.date.accessioned2022-10-31T09:24:16Z-
dc.date.available2022-10-31T09:24:16Z-
dc.date.issued2022-
dc.identifier.citationWelgamage V. R.; Senarathne U. A. C.; Madhubhashani N. H. A. C.; Liyanage T. C.; Dinesh Asanka P. P. G. (2022), Overall and Feature Level Sentiment Analysis of Amazon Product Reviews Using Machine Learning Techniques and Web-Based Chrome Plugin, International Research Conference on Smart Computing and Systems Engineering (SCSE 2022), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. 205-210.en_US
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/25429-
dc.description.abstractOne of the critical tasks of Natural Language Processing (NLP) is sentiment analysis or opinion mining. Sentiment analysis has gained much attention in recent years. It collects data on each user's views, feelings, and opinions regarding a particular product to determine whether they have a positive, neutral, or negative attitude toward it. This study aims to address the categorising sentiment polarity, which is one of the essential issues in sentiment analysis and with extensive process descriptions. The key contribution of this study is to introduce feature-wise sentiment analysis for online products considering the customer reviews and star ratings using the modified web-based chrome plugin. Finally, we share some insight into our future sentiment analysis efforts. The research was based on the categorisation of sentiment polarity in online product reviews from Amazon.comen_US
dc.publisherDepartment of Industrial Management, Faculty of Science, University of Kelaniya Sri Lankaen_US
dc.subjectclassification, feature review, Natural Language Processing (NLP), polarity, product review, sentiment analysis, web-based chrome pluginen_US
dc.titleOverall and Feature Level Sentiment Analysis of Amazon Product Reviews Using Machine Learning Techniques and Web-Based Chrome Pluginen_US
Appears in Collections:Smart Computing and Systems Engineering - 2022 (SCSE 2022)

Files in This Item:
File Description SizeFormat 
SCSE 2022 31.pdf15.32 kBAdobe PDFView/Open
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.