A literature review on text classification and sentiment analysis approaches

Wang Dawei and Rayner Alfred and Joe Henry Obit and Chin Kim On (2021) A literature review on text classification and sentiment analysis approaches. In: International Conference on Computational Science and Technology, ICCST 2020, 29–30 August 2019, Kota Kinabalu, Malaysia.

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Abstract

Sentiment analysis is an important branch task of text classification and the related system usually is applied to in perception of user emotion and public opinion monitoring. By comparison, the text classification can be applied to more fields than sentiment analysis. In the system architecture, same as text classification, the complete classification systemmainly contains data acquisition, data pre-process, feature extraction, classification algorithm and result output.TheWeb crawler usually be used in first step, the URL Link, hashtags, Non-Chinese text should be removed in second step. In feature extraction, the IG, TF-IDF, Word2vec usually be used. Then, the SVM, Naive Bayes, KNN or Neural network algorithm usually be used in classifier. Furthermore, as a system that can run automatically, the sentiment analysis system should be able to extract significant feature from corpus and make accurately analysis about emotional polarity of text corpus. At present, the system improvement direction of related system focuses on 3 aspects: data acquisition, feature extraction and classifier algorithm.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Literature review , Text classification , Sentiment analysis , Classifier algorithm
Subjects: Q Science > QA Mathematics
T Technology > T Technology (General)
Divisions: FACULTY > Faculty of Computing and Informatics
Depositing User: DG MASNIAH AHMAD -
Date Deposited: 23 Jul 2021 04:18
Last Modified: 23 Jul 2021 04:18
URI: http://eprints.ums.edu.my/id/eprint/29989

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