Arabic Sentiment Analysis on Mobile Applications Using Levenshtein Distance Algorithm and Naive Bayes
Author:
Affiliation:
1. Sana'a University,Faculty of Computer and Information Technology,Computer Science Department,Yemen
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9935340/9935129/09935492.pdf?arnumber=9935492
Reference17 articles.
1. An Improved Sentiment Classification Approach for Measuring User Satisfaction toward Governmental Services’ Mobile Apps Using Machine Learning Methods with Feature Engineering and SMOTE Technique
2. Sentiment Analysis on Customer Satisfaction of Digital Banking in Indonesia
3. K-Means Algorithm and Levenshtein Distance Algorithm for Sentiment Analysis of School Zonation System Policy
4. Contextual Analysis of Comments in B2C Facebook Fan Pages Based on the Levenshtein Algorithm
5. An Enhanced Algorithm for Matching Arabic Names Entered by Mobile Phones
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3. A Novel Hybrid Model Based on CNN and Bi-LSTM for Arabic Multi-domain Sentiment Analysis;Complex, Intelligent and Software Intensive Systems;2023
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