Sentiment Analysis Using Natural Language Processing and Machine Learning

Authors

  • Neema George  Department of CSE, MLMCE, Kerala, India
  • Neena Joseph  Department of CSE, MLMCE, Kerala, India
  • Vinodh P Vijayan  Department of CSE, MLMCE, Kerala, India
  • Simy Mary Kurian  Department of CSE, MLMCE, Kerala, India
  • Nimmymol Manuel   Department of CSE, MLMCE, Kerala, India

Keywords:

Sentiment Analysis, Opinion Mining, Stemming, rating prediction, VC dimension, TFIDF

Abstract

Lately, we have seen a twist of online web based business sites. It shows an extraordinary chance to share our surveys and evaluations for different items we buy. Looking to the rating can't the only one help a client to get an outline about the item rather the most ideal route is to peruse the audits about the item. Be that as it may, at that point a fascinating issue comes up. Imagine a scenario where the quantity of surveys is in the hundreds or thousands. Which comprise of10 to 15 pages at that point it's simply not possible to experience each one of those surveys because of wastage of time and exertion. Here comes the significance of audits. To mine profitable data from audits to comprehend a client's inclinations and make a precise end pivotal. In this work, we propose a sentiment based rating expectation technique to take care of this issue.

References

  1. S.Erevelles,N.Fukawa,andL.Swayne,“Bigdataconsumeranalyticsandthetransformationofmarketing,”JournalofBusinessResearch,vol.69,no.2,pp. 897–904, 2016.https://doi.org/10.1016/j.jbusres.2015.07.001
  2. P.Russometal.,“Bigdataanalytics,”TDWIbestpracticesreport,fourthquarter,pp.1–35,2011.
  3. Wang,H.;Lu,Y.;Zhai,C.Latentaspectrating analysisonreviewtextdata:Aratingregressionapproach.InProceedingsofthe16thACMSIGKDDInternationalConferenceonKnowledgeDiscoveryandDataMining,Washington, DC, USA, 25–28 July 2010; pp. 783–792.https://doi.org/10.1145/1835804.1835903
  4. J. Narayanan R, Liu B, Choudhary A (2009) Sentimentanalysis of conditional sentences. In: Proceedings of the2009 conference on empirical methods in natural languageprocessing https://doi.org/10.3115/1699510.1699534
  5. J. Huang, X. Cheng, J. Guo, H. Shen, and K. Yang,“Social recommendation with interpersonal influence,” inProc.19th Eur.Conf.Artif.Intell.,2010,pp.601–606.
  6. T.Kawashima,T.Ogawa,and M.Haseyama,“A ratingpredictionmethodfore-commerceapplicationusingordinalregressionbasedonLDAwithmulti-modalfeatures,” in Proc. IEEE 2nd Global Conf.Consum.Electron.,2013,pp.260–261.https://doi.org/10.1109/GCCE.2013.6664818
  7. B.Wang,Y.Min,Y.Huang,X.Li,andF.Wu,“Reviewratingpredictionbasedonthecontentandweightingstrongsocialrelationofreviewers,”inProc.Int.WorkshopMiningUnstructuredBigDataUsingNaturalLang. Process., 2013, pp. 23–30.https://doi.org/10.1145/2513549.2513554
  8. Bafna,Kushal,andDurgaToshniwal.”Featurebasedsummarizationofcustomersreviewsofonlineproducts.”Procedia Computer Science 22 (2013): 142-151.https://doi.org/10.1016/j.procs.2013.09.090

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-01-30

Issue

Volume 5, Issue 1, January-February-2019

Section

Research Articles

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Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Neema George, Neena Joseph, Vinodh P Vijayan, Simy Mary Kurian, Nimmymol Manuel , " Sentiment Analysis Using Natural Language Processing and Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 1, pp.638-644, January-February-2019.