Statistical Modeling for Sentiment Classification: A Review

Authors

  • Varsha Pal IES College of technology, Bhopal, India
  • Akshay Varkale IES College of technology, Bhopal, India

DOI:

https://doi.org/10.26438/ijcse/v8i10.100105

Keywords:

TPR, FNR, ML, NL, SVM ANN

Abstract

Sentiment classification is the process of using NLP, statistics, or machine learning methods to extract, identify, or otherwise characterize the sentiment content of a text unit. Based on a sample of tweets, how are people responding to this ad campaign/product release/news item? There are several application of opinion mining such as on business intelligence, Politics/political science, Law/policy making, Sociology, Psychology etc. By use of digital platform administration can collect response from consumer and by means of applying opinion mining technique a useful information from user collected data. In this paper we have given a brief review over different work done in the field of sentiment classification and given tabular comparison among different opinion classification technique based on accuracy.

References

[1] B. Vamshi Krishna, Ajeet Kumar Pandey and A. P. Siva Kumar Feature Based Opinion Mining and Sentiment Analysis Using Fuzzy Logic Springer 2018.

[2] Y. Wang, J. Zhang Keyword Extraction from Online Product Reviews Based on Bi-Directional LSTM Recurrent Neural Network IEEE 2017.

[3] Sandra Garcia Esparza , Michael P. O’Mahony, Barry Smyth Mining the real-time web: A novel approach to product recommendation Elsevier 2011.

[4] Isa Maks , Piek Vossen A lexicon model for deep sentiment analysis and opinion mining applications Elsevier 2012.

[5] Rodrigo Moraes, João Francisco Valiati, Wilson P. Gavião Neto Document-level sentiment classification: An empirical comparison between SVM and ANN Elsevier 2013.

[6] Tarik S. Zakzouk Comparing text classifiers for sports news Elsevier 2012.

[7] Ngoc Phuong Chau, Viet Anh Phan, Minh Le Nguyen Deep Learning and Sub-Tee Mining for Document Level Sentiment Classification KSE 2016.

[8] Ivo Danihelka et. al. Associative Long Short-Term Memory arXiv 2016.

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Published

2020-10-31
CITATION
DOI: 10.26438/ijcse/v8i10.100105
Published: 2020-10-31

How to Cite

[1]
V. Pal and A. Varkale, “Statistical Modeling for Sentiment Classification: A Review”, Int. J. Comp. Sci. Eng., vol. 8, no. 10, pp. 100–105, Oct. 2020.

Issue

Vol. 8 No. 10 (2020): IJCSE October Edition

Section

Review Article

License

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