Analyzing the sentiment polarity of watched movies based on viewers’ comments

dc.contributor.authorChabira, safia Supervisor2: Gadri, Said
dc.date.accessioned2021-07-18T10:03:05Z
dc.date.available2021-07-18T10:03:05Z
dc.date.issued2021
dc.description.abstractCustomer product reviews are critical in determining whether or not a customer will buy a product or utilize a service. Others' internet reviews, blogs, and social networking platforms influence customer choices and opinions. Recommender systems are now frequently used in many commercial sites to assist consumers in dealing with the problem of information overload. Users can get tailored recommendations via recommender systems, which can help them, make better selections on which product to buy from a large number of options. In our work, we developed a sentiment analysis model based on the ANN model. Its purpose is to analyze the sentiment polarity of movies comments. This model proved to be highly effective and accurate in the analysis of feelings.en_US
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/25111
dc.language.isoenen_US
dc.publisherUniversity of M'silaen_US
dc.subjectdeep learning, Sentiment analysis, Neural Networks, Machine learning.en_US
dc.titleAnalyzing the sentiment polarity of watched movies based on viewers’ commentsen_US
dc.typeThesisen_US

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