Journal of Engineering and Applied Sciences
Year:
2019
Volume:
14
Issue:
4
Page No.
1182 - 1188
References
Calvin and J. Setiawan, 2014. Using text mining to analyze mobile phone provider service quality (Case Study: Social Media Twitter). Intl. J. Mach. Learn. Comput., 4: 106-109.
CrossRef | Direct Link | Ghiassi, M., J. Skinner and D. Zimbra, 2013. Twitter brand sentiment analysis: A hybrid system using N-gram analysis and dynamic artificial neural network. Expert Syst. Appl., 40: 6266-6282.
Direct Link | Ikonomakis, M., S. Kotsiantis and V. Tampakas, 2005. Text classification using machine learning techniques. WSEAS. Trans. Comput., 4: 966-974.
Direct Link | Kontopoulos, E., C. Berberidis, T. Dergiades and N. Bassiliades, 2013. Ontology-based sentiment analysis of twitter posts. Expert Syst. Appl., 40: 4065-4074.
CrossRef | Direct Link | Lestari, N.M., K.G. Putra and K.A. Chayawan, 2013. Personality types classification for Indonesian text in partners searching website using Naive Bayes methods. Intl. J. Comput. Sci. Issues, 2013: 1-8.
Direct Link | Liu, B., 2012. Sentiment Analysis: A Fascinating Problem. Morgan & Claypool Publishers, Chicago, Illinois,.
Ma’ady, M.N.P., C.K. Yang, R.P. Kusumawardani and H. Suryotrisongko, 2018. Temporal exploration in 2D visualization of emotions on Twitter stream. Telecommun. Comput. Electron. Control, 16: 376-384.
Direct Link | Tan, P.N., S. Michael and K. Vipin, 2006. Introduction to Data Mining. Pearson Education India Ltd., Boston, Massachusetts, ISBN:9780321420527, Pages: 769.