Modified Seagull Optimization With Deep Learning for Affect Classification in Arabic Tweets

Arabic is one of the world's most widely spoken languages, and there is a huge amount of digital content available in Arabic. By the categorization of Arabic documents, it becomes easier to search and access specific content of interest. With the increasing quantity of user-generated content on...

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Vydané v:	IEEE access Ročník 11; s. 98958 - 98968
Hlavní autori:	Al-Onazi, Badriyya B., Alshamrani, Hassan, Aldaajeh, Fatimah Okleh, Aziz, Amira Sayed A., Rizwanullah, Mohammed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Affect analysis Algorithms Arabic tweets Belief networks Classification Data mining Data preprocessing Deep learning Documentation emotion classification Emotion recognition Information retrieval Machine learning Machine translation Natural language processing Optimization Sentiment analysis Social networking (online) Text categorization text classification Tuning User generated content
ISSN:	2169-3536, 2169-3536
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