Sentiment Analysis with Various Deep Learning Models on Movie Reviews
dc.authorscopusid | 57203003458 | en_US |
dc.authorscopusid | 56495320500 | en_US |
dc.contributor.author | Basarslan, M.S. | |
dc.contributor.author | Kayaalp, F. | |
dc.date.accessioned | 2024-08-23T16:07:33Z | |
dc.date.available | 2024-08-23T16:07:33Z | |
dc.date.issued | 2022 | en_US |
dc.department | Düzce Üniversitesi | en_US |
dc.description | 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022 -- 29 December 2022 through 30 December 2022 -- Istanbul -- 188710 | en_US |
dc.description.abstract | Social media have led to the development of artificial intelligence tasks such as sentiment analysis to see whether people's posts have a positive or negative effect on other people. Ideas that affect society directly or indirectly about various domains, such as a movie or a meal, are very important for many business operations. This paper presents a sentiment analysis study which was carried out with 7 models based on various methods of deep learning algorithms on IMDB dataset. The best result was obtained with the model consisting of 2 Bi-LSTM and 2 dropout layers with 80%-20% train-test separation and an accuracy value of 88.21%. © 2022 IEEE. | en_US |
dc.identifier.doi | 10.1109/ICAIoT57170.2022.10121745 | |
dc.identifier.isbn | 979-835039676-8 | en_US |
dc.identifier.scopus | 2-s2.0-85160547538 | en_US |
dc.identifier.scopusquality | N/A | en_US |
dc.identifier.uri | https://doi.org/10.1109/ICAIoT57170.2022.10121745 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12684/14726 | |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | Proceedings - 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Neural Networks | en_US |
dc.subject | Sentiment Analysis | en_US |
dc.subject | Text Representation | en_US |
dc.subject | Learning algorithms | en_US |
dc.subject | Learning systems | en_US |
dc.subject | Long short-term memory | en_US |
dc.subject | Business operation | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Learning models | en_US |
dc.subject | Model-based OPC | en_US |
dc.subject | Movie reviews | en_US |
dc.subject | Neural-networks | en_US |
dc.subject | Sentiment analysis | en_US |
dc.subject | Social media | en_US |
dc.subject | Text representation | en_US |
dc.subject | Sentiment analysis | en_US |
dc.title | Sentiment Analysis with Various Deep Learning Models on Movie Reviews | en_US |
dc.type | Conference Object | en_US |