Sentiment analysis opinion mining using Text Extraction
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Published:
Dec 26, 2020
Keywords:
Opinion Mining, Text Classification, Social Networks, Extraction
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Abstract
This research retrieved the dataset from the Facebook online articles of the tourism by extract positive and negative review words and compares the efficiency of accuracy rate by Naive Bayes K-Nearest Neighbors and decision tree. The result showed the Naive Bayes algorithm accuracy was 87.97% K-Nearest Neighbors accuracy was 83.80 and decision tree algorithm accuracy was 79.89 %. With the result, researchers used the Naive Bayes algorithm to be the prototype for develop the online analysis system and select the twitter online reviews about the Lampang Province legion’s accommodation. The result showed the positive and negative review word extraction system can use functionally.
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How to Cite
Srisawakarn, S., & Srisuay, S. (2020). Sentiment analysis opinion mining using Text Extraction. Journal of Applied Information Technology, 6(2), 95–104. retrieved from https://ph02.tci-thaijo.org/index.php/project-journal/article/view/241838
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References
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(transforms [thesis].) National Institute of Development Administration.(in Thai)
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(วิทยานิพนธ์ปริญญามหาบัณฑิต) สถาบันบัณฑิตพัฒนบริหารศาสตร์
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Unsupervised Classification of Reviews,” in Proc. the 40th Annual Meeting of the
Association for Computational Linguistics, 2002, pp. 417-424.
[5] M. Taboada and J. Grieve, “Analyzing Appraisal Automatically,” in Proc. the AAAI Spring
Symposium, 2004, pp. 158-161.
[6] K. Zhang, R. Narayanan, and A. Choudhary, “Voice of the Customers: Mining Online
Customer Reviews for Product Feature-Based Ranking,” in Proc. the 3rd conference
on Online social networks (WOSN’10), 2010, pp. 11.
[7] M. Hu and B. Liu, “Mining and Summarizing Customer Reviews,” in Proc. the 2004 ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004,
pp. 168-177.
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Hierarchy Process. (2nd edition), Pittsburgh, PA: RWS, 2006, pp. 4-5.
[9] Thongjor N. Machine Learning#2 [Internet].Babel Coder. 2017. Available from:
https://www.babelcoder.com/blog/posts/k-nearest-neighbors
