Skip to main content
SpringerLink
Log in

Resource Creation for Sentiment Analysis of Under-Resourced Language: Marathi

  • Conference paper
  • First Online:
Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1380))

Abstract

With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data are increasing day by day. Mining these data towards the corporate and government has become a broad area of research under Natural Language Processing. Sentiment Analysis (SA), identification of the public’s attitude, using machine learning or subjective lexicon, is easier for resource-rich languages like English. Still, for Marathi being poor resource language, it’s a difficult task. In this research, the three approaches have experimented – Corpus-based, SentiWordNet3.0-based, and Hindi SentiWordNet (HSWN)-based to create the Marathi sentiment lexicon (adjective, adverb). The first two approaches use Google Translator to make use of English resource-SWN3.0. The third approach uses HSWN and Marathi WordNet, which minimizes translation errors. The word coverage of the SWN3.0-based lexicon is noteworthy. This paper attempts the Marathi subjective lexicon creation for the first time, which would aid for SA chore precise to the Marathi data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kashyap, L., Joshi, S.R., Bhattacharyya, P.: Insights on Hindi WordNet coming from the IndoWordNet. In: Dash, N.S., Bhattacharyya, P., Pawar, J.D. (eds.) The WordNet in Indian Languages, pp. 19–44. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-1909-8_2

    Chapter  Google Scholar 

  2. Google Translate. https://translate.google.com

  3. Al-Sallab, A., Baly, R., Hajj, H., Shaban, K.B., El-Hajj, W., Badaro, G.: AROMA: a recursive deep learning model for opinion mining in Arabic as a low resource language. ACM Trans. Asian Low-Resource Lang. Inf. Process. (TALLIP) 16(4), 25:1–25:20 (2017)

    Google Scholar 

  4. Alomari, K.M., ElSherif, H.M., Shaalan, K.: Arabic tweets sentimental analysis using machine learning. In: Benferhat, S., Tabia, K., Ali, M. (eds.) IEA/AIE 2017. LNCS (LNAI), vol. 10350, pp. 602–610. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60042-0_66

    Chapter  Google Scholar 

  5. Saif M., Salameh, M., Kiritchenko, S.: Sentiment lexicons for Arabic social media. In: Proceedings of the 10th Edition of the Language Resources and Evaluation Conference (LREC), pp. 33–37. Portoroz, Slovenia LREC (2016)

    Google Scholar 

  6. Baccianella, S., Esuli, A., Sebastiani, F.: SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC 2010), pp. 2200–2204. European Languages Resources Association (ELRA), Valletta, Malta (2010)

    Google Scholar 

  7. Liu, B.: Handbook of Natural Language Processing, 2nd eds. CRC Press, Taylor and Francis Group, Boca Raton (2010)

    Google Scholar 

  8. Medagoda, N., Shanmuganathan, S., Whalley, J.: Sentiment lexicon construction using SentiWordNet 3.0. In: Proceedings of 11th International Conference on Natural Computation (ICNC), pp. 802–807. IEEE, Zhangjiajie (2015)

    Google Scholar 

  9. Bakliwal, A., Arora, P., Varma, V.: Hindi subjective lexicon: a lexical resource for Hindi polarity classification. In: Proceedings of the Eighth International Conference on Language Resources and Evaluation Conference (LREC), pp. 1189–1196. Istanbul, Turkey (2012)

    Google Scholar 

  10. Kim, S.M., Hovy, E.: Identifying and analyzing judgment opinions. In: Proceedings of HLT/NAACL-2006, pp. 200–207. ACL, NY (2006)

    Google Scholar 

  11. Karthikeyan, A.: Hindi English wordnet linkage (2010)

    Google Scholar 

  12. Benamara, F., Cesarano, C., Picariello, A., Reforgiato, D., Subrahmanian, V.: Sentiment analysis: adjectives and adverbs are better than adjectives alone. In: Proceedings of the International Conference on Weblogs and Social Media (ICWSM), pp. 1–7. ICWSM, Boulder, CO (2007)

    Google Scholar 

  13. Mahanty, G., Kannan, A., Mamidi, R.: Building a SentiWordNet for Odia. In: Proceedings of 8th Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media Analysis, pp. 143–148. Association for Computational Linguistics (ACL), Copenhagen, Denmark (2017)

    Google Scholar 

  14. Das, A., Bandyopadhyay, S.: SentiWordNet for Indian languages. In: Proceedings of the 8th Workshop on Asian Language Resources, pp. 56–63. Coling 2010 Organizing Committee, Beijing, China (2010)

    Google Scholar 

  15. Popale, L., Bhattacharyya, P.: Creating Marathi WordNet. In: Dash, N.S., Bhattacharyya, P., Pawar, J.D. (eds.) The WordNet in Indian Languages, pp. 147–166. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-1909-8_8

    Chapter  Google Scholar 

  16. Joshi, A., Balamurali, A.R., Bhattacharyya, P.: A fall-back strategy for sentiment analysis in Hindi: a case study. In: Proceedings 8th International Conference on Natural Language Processing, ICON (2010)

    Google Scholar 

  17. El-Haj, M., Kruschwitz, U., Fox, C.: Creating language resources for under-resourced languages: methodologies, and experiments with Arabic. Lang. Resourc. Eval. 49(3), 549–580 (2014). https://doi.org/10.1007/s10579-014-9274-3

    Article  Google Scholar 

  18. Al-Thubaity, A., Alqahtani, Q., Alijandal, A.: Sentiment lexicon for sentiment analysis of Saudi dialect tweets. In: Proceedings of the Fourth International Conference on Arabic Computational Linguistics (ACLing 2018), pp. 301–307. Elsevier, Dubai, United Arab Emirates (2018)

    Google Scholar 

  19. Wikipedia contributors, “Cohen's kappa” Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Cohen%27s_kappa&oldid=928044732. Accessed 29 Nov 2019

  20. Xu, G., Yu, Z., Yao, H., Li, F., Meng, Y., Xu, W.: Chinese text sentiment analysis based on extended sentiment dictionary. IEEE Access 7, 43749–43762 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India

    Rupali S. Patil & Satish R. Kolhe

Authors
  1. Rupali S. Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Satish R. Kolhe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rupali S. Patil .

Editor information

Editors and Affiliations

  1. University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India

    Bharti Gawali

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Patil, R.S., Kolhe, S.R. (2021). Resource Creation for Sentiment Analysis of Under-Resourced Language: Marathi. In: Santosh, K.C., Gawali, B. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2020. Communications in Computer and Information Science, vol 1380. Springer, Singapore. https://doi.org/10.1007/978-981-16-0507-9_37

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-0507-9_37

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0506-2

  • Online ISBN: 978-981-16-0507-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation