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dc.contributor.advisorEvren Güneyen_US
dc.contributor.authorAtik, Anılcan
dc.date.accessioned2021-12-14T11:21:13Z
dc.date.available2021-12-14T11:21:13Z
dc.date.issued2021en_US
dc.identifier.citationAtik, A. (2021). Yelp Review Dataset Sentiment Analysis Using Machine Learning Techniques. MEF Üniversitesi Fen Bilimleri Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı. ss. 1-22en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1693
dc.description.abstractToday, internet review sites are becoming a significant criterion for users’ consumption habits on products and services, while being vital source of feedback for businesses. This project aims to present quick feedback on whether consumers are satisfied with businesses’ product and services, lessen the allocation of resources on information extraction towards these reviews, and provide a more agile environment for businesses, by automatizing the extraction of the information “whether the sentiment towards the business service or product is positive or negative” from textual data. The problem, binary classification out of textual data, is addressed through Yelp Company reviews dataset. Yelp is an internet review website, it enables users to review products, services, and businesses. Alongside with the text formatted restaurant reviews, star-rating is converted to 1 (positive) and 0 (negative). These values are obtained to provide the target column to predict the sentiment of the review text. 100,000 restaurant review records are used in 4 different machine learning algorithms to predict the binary classification problem of predicting whether the review sentiment is positive or negative. 2 neural networks one with pre-trained GloVe, SVM, and Logistic Regression models are used, and the success of these models is compared using F1-Score as a performance metric. These results are presented in the paper.en_US
dc.language.isoengen_US
dc.publisherMEF Üniversitesi Fen Bilimleri Enstitüsüen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectYelp Reviews, Supervised Learning, Sentiment Analysisen_US
dc.titleYelp review dataset sentiment analysis using machine learning techniquesen_US
dc.title.alternativeYelp yorumlar verisetinin makine öğrenmesi teknikleri kullanılarak duygu analizien_US
dc.typeYL-Bitirme Projesien_US
dc.departmentBüyük Veri Analitiği Yüksek Lisans Programıen_US
dc.identifier.startpage1-22en_US
dc.relation.publicationcategoryYL-Bitirme Projesien_US
dc.contributor.institutionauthorAtik, Anılcan


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