Feature selection based on particle swarm optimization algorithm for sentiment analysis classification

• Main Authors: Nurcahyawati, Vivine, Mustaffa, Zuriani
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2021
• Subjects: QA76 Computer software; TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/36779/1/Feature%20Selection%20based%20on%20Particle%20Swarm%20Optimization_FULL.pdf; http://umpir.ump.edu.my/id/eprint/36779/2/Feature%20selection%20based%20on%20particle%20swarm%20optimization%20.pdf; http://umpir.ump.edu.my/id/eprint/36779/; https://doi.org/10.1109/ITSS-IoE53029.2021.9615311
• Institution: Universiti Malaysia Pahang

Online media serve as a potential secondary data source for studies on sentiment analysis. The current conditions of the data sources are very different, and it offers a variety of writing systems. Therefore, the results of accuracy in sentiment analysis are very important. An improved approach was...