A Review on Punjabi Language Sentiment Analysis Using Machine Learning

Abstract

In this computer era, everyone is expressing their opinions or sentiments not only physically but over the social media platforms very frequently. Earlier, English was the only language for exchanging thoughts over the web, however, in the recent times, feedbacks, surveys or comments by the users are expressed in regional languages too. This leads to the need of analyzing sentiments for better communication on the digital platforms. For example, if someone wants to book a hotel for a day, he may check for feedbacks and ratings for making his final decision. Sentiment analysis is the study that clarifies and categorizes views, feelings, and judgements in written information. Over the last decade, research into semantic analysis in the English language has expanded rapidly. Additionally, the number of online users who create content has been rising, engaging not only in English but also in their native languages. Most of the paperwork completed there to date has been in English, but there has been limited research in the field of Indian regional languages, particularly Punjabi. In this study, we explored different methods employed to carry out opinion research and investigative work for vernacular languages like Hindi, Bengali, Punjabi and many more. Numerous deep learning and lexicon-based strategies have been suggested in the literature to automate the sentiment analysis process.

1. Kaur A and Gupta V. A survey on sentiment analysis and opinion mining techniques. Journal of Emerging Technologies in Web Intelligence (JETWI). 2013. Vol. 5. pp. 367–71

   [1]

2. Mukherjee S and Bhattacharyya P. Sentiment analysis: A literature survey. arXiv preprint arXiv:1304.4520. 2013

   [2]

3. Pang B and Lee L. Opinion mining and sentiment analysis. Found Trends Inf Retr. 2008. Vol. 2. pp. 1-35

   [3]

4. Karamibekr M and Ghorbani AA. Sentiment analysis of social issues. In 2012 IEEE international conference on social informatics. 2012. pp. 215-221

   [4]

5. Sandhu JK and Garg P. Quality Evaluation of Product Reviews using Sentiment Analysis. Int J Latest Trends Eng Technol. 2022. Vol. 20. pp. 018–022

   [5]

6. Dadvar M, Hauff C and De Jong FM. Scope of negation detection in sentiment analysis. In 11th Dutch-Belgian Information Retrieval Workshop, DIR 2011; University of Amsterdam. 2011. pp. 16-20

   [6]

7. Yi J, Nasukawa T, Bunescu R and Niblack W. Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques. In Third IEEE international conference on data mining. 2003. pp. 427–434

   [7]

8. Singh M, Goyal V and Raj S. Sentiment analysis of english-punjabi code-mixed social media content to predict elections. In Advances in Information Communication Technology and Computing: Proceedings of AICTC 2019. Singapore: Springer. 2021. pp. 81–90

   [8]

9. Kaur A and Gupta V. Proposed algorithm of sentiment analysis for Punjabi text. Journal of Emerging Technologies in Web Intelligence (JETWI). 2014. Vol. 6. pp. 180-3

   [9]

10. Soumya S and Pramod KV. Sentiment analysis of Malayalam tweets using machine learning techniques. ICT Express. 2020. Vol. 6. pp. 300-5

    [10]

11. Arora P and Kaur B. Sentiment analysis of political reviews in Punjabi language. Int J Comput Appl. 2015. Vol. 126. pp. 20–23

    [11]

12. Kaur G and Kaur K. Sentiment detection from Punjabi text using support vector machine. Int J Sci Res Comput Sci Eng. 2017. Vol. 5. pp. 39–46

    [12]

13. Chopra FK and Bhatia R. A critical review of sentiment analysis. Int J Comput Appl. 2016. Vol. 149. pp. 37-40

    [13]

14. Sharma A. Sentiment analyzer using Punjabi language. International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE). 2014. Vol. 2. pp. 5904–9

    [14]

15. Jain EU and Sandu A. Emotion detection from Punjabi Text using hybrid support vector Machine and maximum entropy algorithm. International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE). 2015. Vol. 4. pp. 89–93

    [15]

16. Deepali NG. Movie review mining in Punjabi. International Journal of Application or Innovation in Engineering and Management (IJAIEM). 2013. Vol. 2. pp. 372–375

    [16]

17. Chopra FK and Bhatia R. Sentiment analyzing by dictionary based approach. Int J Comput Appl. 2016. Vol. 152. pp. 32-4

    [17]

18. Das A and Bandyopadhyay S. Sentiwordnet for bangla. Knowledge Sharing Event-4: Task. 2010. Vol. 2. pp. 1-8

    [18]

19. Cambria E, Poria S, Gelbukh A and Thelwall M. Sentiment analysis is a big suitcase. IEEE Intell Syst. 2018. Vol. 32. pp. 74–80

    [19]

20. Ganeshbhai SY and Shah BK. Feature based opinion mining: A survey. In 2015 IEEE International Advance Computing Conference (IACC). 2015. pp. 919–923

    [20]