Sentiment Analysis in the AI-Based Social Networks
| Autor: | Kamelya Dehghani Kohneh Shahri, Mohammad-Ali Afshar Kazemi, Ali Reza Pourebrahimi |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | International Journal of Information Science and Management, Vol 22, Iss 4, Pp 287-307 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2008-8302 2008-8310 |
| DOI: | 10.22034/ijism.2024.2019923.1360 |
| Popis: | Recent developments in emerging technologies have enabled users to interact with social networks. Nowadays, one of the ways of interaction is to understand the real feelings of people at the moment, the outcome of which, based on the people’s reaction and attitude, appears in analyzing feelings like facial features, type of speech, or the people’s jobs such as video, photograph, voice, and text. In this research, through deep learning and machine learning in the AI, the sentiment analysis has been studied and evaluated using AI and deep learning algorithms like motion detection, body language recognition, image processing, sound and text processing, computer vision, natural language processing and different network techniques. The paper, providing a new conceptual model design, has provided more details about sentiment analysis in social networks by incorporating AI techniques in social networks with high speed and accuracy. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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