Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 08, August 2024

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

Sentiment Analysis and its Challenges

Author : Ravneet Kaur 1 Gaurav Gupta 2 Gurjit Singh 3

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Date of Publication :7th February 2017

Abstract: Sentiment analysis is the wide study area in educational and commercial fields. The word sentiment speaks of about the emotion or views of the public towards the particular area or field. So it is also called as opinion mining i.e. to mine the opinion of public to collect the required knowledge. Sentiment analysis can be used in any field. Earlier research is carried out to find the public sentiments. With enhancement sentiment analysis can become a useful area for research. Here we analyze previous research and interpret their results and also explain the various classification algorithms that are widely used for sentiment classification like Naive Bayes, Support Vector Machines (SVM) and K-NN classifier. Also the methodology for the sentiment analysis is explained using proper steps and examples. This paper also discusses the application areas and challenges in the field of sentiment analysis.

Reference :

    1. BholaneSavitaDattu and Prof. Deipali V. Gore, "A Survey on Sentiment Analysis on Twitter Data Using Different Techniques", International Journal of Computer Science and Information Technologies, Vol. 6, 2015.
    2. RushleneKaurBakshi, Ravneetkaur, Navneetkaur and Gurpreetkaur, "Opinion Mining and Sentiment Analysis", IEEE Third International Conference, 2016.
    3. PragyaTripathi, Santosh Kr Vishwakarma and Ajay Lala,"Sentiment Analysis of English Tweets Using Rapid Miner", IEEE International conference, 2015.
    4. Shubhi Mittal, AshnaGoel and RachnaJain,"Sentiment Analysis of E-commerce and Social Networking Sites",IEEE Third International Conference, 2016.
    5. Shachi H Kumar, "Twitter Sentiment analysis", CMPS 242 Project Report.
    6. TanuVerma, Renuand Deepti Gaur, " Tokenization and Filtering Process in RapidMiner", International Journal of Applied Information Systems (IJAIS), Volume 7– No. 2, April 2014.
    7. Xindong Wu, Vipinkumar, JoydeepGhosh,"Top 10 algorithms in Data Mining", Springer-Verlag London Limited 2007, Dec 2007.
    8. https://rayli.net/blog/data/top-10-data-mining-algorithmsin-plain-english/
    9. GautamiTripathi and Naganna S2, "Opinion Mining: A Review", International Journal of Information & Computation Technology, vol. 4, pp. 1625-1635, 2014.
    10. Nidhi R. Sharma, Prof. Vidya D. Chitre, "Opinion Mining Analysis and its Challenges", International Journal of Innovations & Advancement in Computer Science, vol. 3, Issue 1, April 2014.
    11. HaseenaRahmath P, "Opinion Mining and Sentiment Analysis – Challenges and Applications", International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol. 3, Issue 5, pp. 401-403, May 2014.
    12. DongSung Kim and Jong Woo Kim, "Public Opinion Mining on Social Media: A Case Study of Twitter Opinion on Nuclear Power", Advanced Science and Technology Letters, Vol.51 (CESCUBE 2014), pp.224-228, 2014.
    13. Rushabh Shah and Bhoomit Patel, "Procedure of Opinion Mining and Sentiment Analysis: A Study", International Journal of Current Engineering and Technology, vol. 4, No. 6, pp.4086-4090, December 2014.
    14. Sakshikalra, Rajesh Sachdeva and Anjali Dhawan, "A Review: Sentiment Analysis and Opinion Mining", International Journal of Research in Engineering and Applied Sciences (IJREAS), Vol. 6 Issue 10, pp. 16-21, October - 2016.
    15. Meghachauhan, "Opinion mining for effective product selection", International Journal of Advance Engineering and Research Development, vol. 3, Issue 4, pp. 429-433, April -2016.
    16. BlessySelvam, S.Abirami, "A Survey on opinion mining framework ", International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 9, pp. 3544-3549, September 2013.
    17. Diana Maynard and Adam Funk, "Automatic Detection of Political Opinions in Tweets", ESWC'11 Proceedings of 8th international conference on The Semantic Web, Pages 88-99.
    18. B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up?: sentiment classification using machine learning techniques,” Proceedings of the ACL-02 conference on Empirical methods in natural language processing, vol.10, pp. 79-86, 2002.
    19. P.D. Turney, “Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews.” Proceedings of the Association for Computational Linguistics (ACL), pp. 417–424, 2002.

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