A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities.

Ali, Ishfaq; Asif, Muhammad; Hamid, Isma; Sarwar, Muhammad Umer; Khan, Fakhri Alam; Ghadi, Yazeed

Ali, Ishfaq; Asif, Muhammad; Hamid, Isma; Sarwar, Muhammad Umer; Khan, Fakhri Alam; Ghadi, Yazeed.

Afiliación

Ali I; Department of Computer Science, National Textile University, Faisalabad, Punjab, Pakistan.
Asif M; Department of Computer Science, National Textile University, Faisalabad, Punjab, Pakistan.
Hamid I; Department of Computer Science, National Textile University, Faisalabad, Punjab, Pakistan.
Sarwar MU; Department of Computer Science, Government College University, Faisalabad, Punjab, Pakistan.
Khan FA; Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Ghadi Y; Department of Software Engineering/Computer Science, Al Ain University, Al Ain, UAE.

PeerJ Comput Sci ; 8: e838, 2022.

Article en En | MEDLINE | ID: mdl-35494844

Palabras clave

Computer aided design; Islamophobic; Mobile and ubiquitous computing; Natural language processing; News stories; Sentiment analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: PeerJ Comput Sci Año: 2022 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Estados Unidos

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