Go-Food Sentiment Analysis Using Twitter Data, Compared the Performance of the Random Forest Algorithm with That of the Linear Support Vector Classifier-Reference-Cited by-同舟云学术

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Go-Food Sentiment Analysis Using Twitter Data, Compared the Performance of the Random Forest Algorithm with That of the Linear Support Vector Classifier

Published:2022 Issue: Volume: Page:3-13
ISSN:
Container-title:Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science)
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Author:

Hadi Muhammad Abdullah^ORCID,Anwar Nizirwan^ORCID,Tjahjono Budi^ORCID,Lina ^ORCID,Sekti Binastya Anggara^ORCID,Achmad Yunita Fauzi^ORCID,Yulhendri ^ORCID

Publisher

Atlantis Press International BV

Reference32 articles.

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2. A. M. Ramadhani and H. S. Goo.: Twitter sentiment analysis using deep learning methods, In: 2017 7th International Annual Engineering Seminar (InAES), pp. 1–4 (2017)

3. A. K. Keshri, B. K. Mishra, and B. P. Rukhaiyar.: When rumors create chaos in e-commerce, Chaos, Solitons and Fractals, vol. 131, no. xxxx, p. 109497 (2020)

4. L. Yang, Y. Li, J. Wang, and R. S. Sherratt.: Sentiment Analysis for E-Commerce Product Reviews in Chinese Based on Sentiment Lexicon and Deep Learning, IEEE Access, vol. 8, pp. 23522–23530 (2020)

5. P. Ji, H. Y. Zhang, and J. Q. Wang.: A Fuzzy Decision Support Model with Sentiment Analysis for Items Comparison in e-Commerce: The Case Study of http://PConline.com, IEEE Trans. Syst. Man, Cybern. Syst., vol. 49, no. 10, pp. 1993–2004 (2019)

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