Intelligent Hybrid Feature Selection for Textual Sentiment Classification
Sentiment Analysis (SA) aims to extract useful information from online Unstructured User-Generated Contents (UUGC) and classify them into positive and negative classes. State-of-the-art techniques for SA suffer a high dimensional feature space because of noisy and irrelevant features from the UUGC....
Main Authors: | Jawad Khan, Aftab Alam, Youngmoon Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9564065/ |
Similar Items
-
Sentiment and Context-Aware Hybrid DNN With Attention for Text Sentiment Classification
by: Jawad Khan, et al.
Published: (2023-01-01) -
Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis
by: Łukasz Augustyniak, et al.
Published: (2015-12-01) -
Sentiment-Aware Word Embedding for Emotion Classification
by: Xingliang Mao, et al.
Published: (2019-03-01) -
GENERATING A MALAY SENTIMENT LEXICON BASED ON WORDNET
by: Nur Sharmini Alexander, et al.
Published: (2017-06-01) -
A Semantic Conceptualization Using Tagged Bag-of-Concepts for Sentiment Analysis
by: Yassin S. Mehanna, et al.
Published: (2021-01-01)