Tweet Sentiment Classification by Semantic and Frequency Base Features Using Hybrid Classifier-Reference-Cited by-同舟云学术

Tweet Sentiment Classification by Semantic and Frequency Base Features Using Hybrid Classifier

Published:2019-11-02 Issue: Volume: Page:107-123
ISSN:2194-5357
Container-title:First International Conference on Sustainable Technologies for Computational Intelligence
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Author:

Menaria Hemant Kumar,Nagar Pritesh,Patel Mayank

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0029-9_9

Reference13 articles.

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2. Shidaganti, G., Hulkund, R.G., Prakash, S.: Analysis and exploitation of twitter data using machine learning techniques. In: International Proceedings on Advances in Soft Computing, Intelligent Systems and Applications, pp. 135–146. Springer, Singapore (2018)

3. Rout, J.K., Choo, K.K.R., Dash, A.K., Bakshi, S., Jena, S.K., Williams, K.L.: A model for sentiment and emotion analysis of unstructured social media text. Electron. Commer. Res. 18(1), 181–199 (2018)

4. Mumtaz, D., Ahuja, B.: A Lexical and Machine Learning-Based Hybrid System for Sentiment Analysis, vol. 713. Springer, Singapore (2018)

5. Al-Smadi, M., Al-Ayyoub, M., Al-Sarhan, H., Jararwell, Y.: An aspect-based sentiment analysis approach to evaluating Arabic news affect on readers. J. Univers. Comput. Sci. 22(5), 630–649 (2016)

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