SENTIMENT ANALYSIS BASED ON DEEP LEARNING
| dc.contributor.author | BENTOUMI, BILAL | |
| dc.contributor.author | GHANAI, ZAKARYA | |
| dc.contributor.author | Supervisor: BOUZAROURA, Ahlem | |
| dc.date.accessioned | 2024-02-26T09:22:54Z | |
| dc.date.available | 2024-02-26T09:22:54Z | |
| dc.date.issued | 2021-06-10 | |
| dc.description.abstract | Sentiment Analysis and Opinion Mining is an emerging field, in recent years several research studies have focused on the task of sentiment analysis, especially in the field of microblogging. Our work is part of this same research axis, we propose a system of subjective classification of the opinions of users of the twitter social network on a product or an event in three categories: positive, negative and neutral. Our contribution consists in integration of deep learning methods besides Naturel Language Processing methods. Our sentiment analysis system is still in the development phase and far from complete. For improvement, we propose the use of hybrid approaches to have better results, and possibly expand the use of this work towards other objectives such as trend analysis and knowledge extraction from social networks. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/42467 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of M'sila | en_US |
| dc.title | SENTIMENT ANALYSIS BASED ON DEEP LEARNING | en_US |
| dc.type | Thesis | en_US |
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