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...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE access Vol. 11; pp. 98958 - 98968
Main Authors:	Al-Onazi, Badriyya B., Alshamrani, Hassan, Aldaajeh, Fatimah Okleh, Aziz, Amira Sayed A., Rizwanullah, Mohammed
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!