Mobile QR Code QR CODE

※ The user interface design of www.ieiespc.org has been recently revised and updated. Please contact inter@theieie.org for any inquiries regarding paper submission.

Journal Search

  1. Home
  2. Archive
  3. 2022-04 (Vol.11 No.02)
  4. 10.5573/IEIESPC.2022.11.2.79
XML PDF INFO REF

REFERENCES

1 
Dey L., Chakraborty S., Biswas A., Bose B., Tiwari S., 2016, Sentiment analysis of review datasets using naive bayes and k-nn classifier, arXiv preprint arXiv:1610.09982., Vol. 09982URL
2 
Ahmad M., Aftab S., Ali I., 2017, Sentiment analysis of tweets using svm, Int J Comput Appl, Vol. 177, No. 5, pp. 25-29URL
3 
Bird J. J., Ekart A., Buckingham C. D., Faria D. R., 2019, July, High resolution sentiment analysis by ensemble classification, In Intelligent Computing-Proceedings of the Computing Conference (pp. 593-606). Springer, Cham.DOI
4 
Ullah M. A., Marium S. M., Begum S. A., Dipa N. S., 2020, An algorithm and method for sentiment analysis using the text and emoticon, ICT ExpressDOI
5 
Singh R., Goel V., 2019, Various machine learning algorithms for twitter sentiment analysis, In Information and Communication Technology for Competitive Strategies. Springer, Singapore., pp. 763-772DOI
6 
Jagdale R. S., Shirsat V. S., Deshmukh S. N., 2019, Sentiment analysis on product reviews using machine learning techniques, In Cognitive Informatics and Soft Computing. Springer. Singapore, pp. 639-647DOI
7 
Nguyen H. T., Le Nguyen M., 2019, An ensemble method with sentiment features and clustering support, Neurocomputing, Vol. 370, pp. 155-165DOI
8 
Abbas M., Memon K. A., Jamali A. A., Memon S., Ahmed A., 2019, Multinomial Naive Bayes classification model for sentiment analysis, IJCSNS, Vol. 19, No. 3, pp. 62URL
9 
Wankhade M., Rao A. C. S., Dara S., Kaushik B., 2017, A Sentiment Analysis of Food Review using Logistic RegressionURL
10 
Tyagi A., Sharma N., 2018, Sentiment Analysis using logistic regression and effective word score heuristic, Int J Eng Technol, Vol. 7, pp. 20-23URL
11 
Minaee S., Azimi E., Abdolrashidi A., 2019, Deep-sentiment: Sentiment analysis using ensemble of cnn and bi-lstm models, arXiv preprint arXiv:1904, Vol. 04206DOI
12 
Abbas A. K., Salih A. K., Hussein H. A., Hussein Q. M., Abdulwahhab S. A., 2020, Twitter Sentiment Analysis Using an Ensemble Majority Vote Classifier, Journal of Southwest Jiaotong University, Vol. 55, No. 1DOI
13 
Katsarou K., Shekhawat D. S., 2019, November, CRD-SentEnse: Cross-domain Sentiment Analysis using an Ensemble Model, In Proceedings of the 11th International Conference on Management of Digital EcoSystems, pp. 88-94DOI
14 
Medhat W., Hassan A., Korashy H., 2014, Sentiment analysis algorithms and applications: A survey, Ain Shams engineering journal, Vol. 5, No. 4, pp. 1093-1113DOI
15 
Alessia D., Ferri F., Grifoni P., Guzzo T., 2015, Approaches, tools and applications for sentiment analysis implementation, International Journal of Computer Applications, Vol. 125, No. 3URL
16 
Osisanwo F. Y., Akinsola J. E. T., Awodele O., Hinmikaiye J. O., Olakanmi O., Akinjobi J., 2017, Supervised machine learning algorithms: classification and comparison, International Journal of Computer Trends and Technology (IJCTT, Vol. 48, No. 3, pp. 128-138URL
17 
Lee H. Y., Renganathan H., 2011, November, Chinese sentiment analysis using maximum entropy, In Proceedings of the Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2011), pp. 89-93URL
18 
Ramadhan W. P., Novianty S. A., Setianingsih S. C., 2017 September, Sentiment analysis using multinomial logistic regression, In 2017 International Conference on Control, Electronics Renewable Energy and Communications (ICCREC), Vol. ieee, pp. 46-49DOI
19 
Riaz S., Fatima M., Kamran M., Nisar M. W., 2019, Opinion mining on large scale data using sentiment analysis and k-means clustering, Cluster Computing, Vol. 22, No. 3, pp. 7149-7164DOI
20 
Li G., Liu F., 2012, Application of a clustering method on sentiment analysis, Journal of Information Science, Vol. 38, No. 2, pp. 127-139DOI
21 
Troussas C., Virvou M., Espinosa K. J., Llaguno K., Caro J., 2013, July, Sentiment analysis of Facebook statuses using Naive Bayes classifier for language learning, In IISA 2013 IEEE, pp. 1-6DOI
22 
Mubarok M. S., Adiwijaya , Aldhi M. D., 2017, August, Aspect-based sentiment analysis to review products using Naive Bayes, In AIP Conference Proceedings, AIP Publishing LLC, Vol. 1867, No. 1, pp. 020060DOI
23 
Sridhar S., Sanagavarapu S., 2020, September, Sentiment Analysis Using Ensemble-Hybrid Model with Hypernym Based Feature Engineering, In 2020 FORTEI-International Conference on Electrical Engineering (FORTEI-ICEE) IEEE, pp. 13-18DOI
24 
Hoang M., Bihorac O. A., Rouces J., 2019, Aspect-based sentiment analysis using bert, In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pp. 187-196URL
25 
Kanakaraj M., Guddeti R. M. R., 2015 February, Performance analysis of Ensemble methods on Twitter sentiment analysis using NLP techniques, In Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) IEEE, Vol. ieee, pp. 169-170DOI
26 
Coletta L. F., Sommaggio N. F. F. d., Hruschka E. R., Hruschka E. R., 2014, Combining classification and clustering for tweet sentiment analysis, Intelligent Systems 2014 Brazilian Conference on. IEEE, pp. 210-215DOI