Predicting customer sentiment: the fusion of deep learning and a fuzzy system for sentiment analysis of Arabic text
Understanding client feedback and satisfaction is a critical concern for any business organization operating in the highly competitive internet industry. Notably, social media platforms such as X (Twitter) act as forums for customers to voice their opinions. Analyzing such feedback is beneficial sin...
Published in: | SOCIAL NETWORK ANALYSIS AND MINING |
---|---|
Main Authors: | Ambreen, Shela; Iqbal, Muhammad; Asghar, Muhammad Zubair; Mazhar, Tehseen; Khattak, Umar Farooq; Khan, Muhammad Amir; Hamam, Habib |
Format: | Article |
Language: | English |
Published: |
SPRINGER WIEN
2024
|
Subjects: | |
Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001335841500001 |
Similar Items
-
Predicting customer sentiment: the fusion of deep learning and a fuzzy system for sentiment analysis of Arabic text
by: Ambreen S.; Iqbal M.; Asghar M.Z.; Mazhar T.; Khattak U.F.; Khan M.A.; Hamam H.
Published: (2024) -
Optimal feature selection for heart disease prediction using modified Artificial Bee colony (M-ABC) and K-nearest neighbors (KNN)
by: Khan, et al.
Published: (2024) -
DenseHillNet: a lightweight CNN for accurate classification of natural images
by: Saqib, et al.
Published: (2024) -
The role of blockchain to secure internet of medical things
by: Ghadi, et al.
Published: (2024) -
Antenna systems for IoT applications: a review
by: Khan, et al.
Published: (2024)