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Kannada Sentiment Analysis Using Vectorization and Machine Learning

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Sentimental Analysis and Deep Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1408))

Abstract

The sentiment analysis (SA) also known as opinion mining (OM) is a new arena in text mining and NLP field. We are presenting a method to analyze the IMDB movie reviews translated to Kannada using Google translator along with other reviews collected from various creditable sites like Vijayakarnataka, Gadgetloka, and filmibeats. In sentiment analysis, many research has been carried out on English text. Methods and resources of English may not produce good results for other languages. In this paper, we are analyzing around 50,034 of reviews with positive and negative labels. Our ensemble classification technique using various vectorization has achieved the accuracy of 89%.

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References

  1. Wang, D., Su, J., & Yu, H. (2020). Feature extraction and analysis of natural language processing for deep learning english language. IEEE Access, 8, 46335–46345. https://doi.org/10.1109/ACCESS.2020.2974101

    Article  Google Scholar 

  2. Ghani, N. A., Hamid, S., Hashem, I. A. T., & Ahmed, E. (2019) Social media big data analytics: A survey. Computers in Human Behavior, 101, 417–428. ISSN 0747–5632.

    Google Scholar 

  3. Sağlam, F., Sever, H., & Genç, B. (2016). Developing Turkish sentiment lexicon for sentiment analysis using online news media. In 2016 IEEE/ACS 13th international conference of computer systems and applications (AICCSA) (pp. 1–5). https://doi.org/10.1109/AICCSA.2016.7945670.

  4. Smetanin, S., & Komarov, M. (2019). Sentiment analysis of product reviews in Russian using convolutional neural networks. In 2019 IEEE 21st conference on business informatics (CBI) (pp 482–486). https://doi.org/10.1109/CBI.2019.00062.

  5. Sabra, K. S., Zantout, R. N., Abed, M. A. E., & Hamandi, L. (2017). Sentiment analysis: Arabic sentiment lexicons. Sensors Networks Smart and Emerging Technologies (SENSET), 2017, 1–4. https://doi.org/10.1109/SENSET.2017.8125054

    Article  Google Scholar 

  6. Das, A., & Bandyopadhyay, S. (2010). SentiWordNet for Bangla.

    Google Scholar 

  7. Das, D., & Bandyopadhyay, S. (2010) Labeling emotion in bengali blog corpus a fine grained tagging at sentence level. In Proceedings of the eighth workshop on Asian language resouces (pp. 47–55). Coling 2010 Organizing Committee, August 2010.

    Google Scholar 

  8. Hegde, Y., & Padma, S. K. (2017). Sentiment analysis using random forest ensemble for mobile product reviews in Kannada. In 2017 IEEE 7th international advance computing conference (IACC) (pp. 777–782).

    Google Scholar 

  9. Anil Kumar, K. M., Rajasimha, N., Reddy, M., Rajanarayana, A., & Nadgir, K. (2015). Analysis of users’ sentiments from Kannada web documents. Procedia Computer Science, 54, 247–256.

    Google Scholar 

  10. Rohini, V., Thomas, M., & Latha, C. (2016). Domain based sentiment analysis in Regional Language- Kannada. International Journal of Engineering Research & Technology (IJERT), 4(22).

    Google Scholar 

  11. Reddy, S., & Sharoff, S. (2011). Cross language POS taggers (and other Tools) for Indian languages: An experiment with Kannada using Telugu resources. In Proceedings of the 5th international joint conference on natural language processing (pp. 11–19), November 8–12, 2011.

    Google Scholar 

  12. Padma, M. C., & Prathibha, R. J. (2014). Development of morphological stemmer, analyzer and generator for Kannada nouns. In Emerging research in electronics, computer science and technology (pp. 713–723).

    Google Scholar 

  13. Xu, J., & Du, Q. (2019). A deep Investigation into fastText. In 2019 IEEE 21st international conference on high performance computing and communications; IEEE 17th international conference on smart city; IEEE 5th International conference on data science and systems (HPCC/SmartCity/DSS) (pp. 1714–1719). https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00234.

  14. Han, J., Pei, J. & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, PESITM, Shivamogga, India

    M. E. Sunil

  2. Information Science and Engineering, PESCE, Mandya, India

    S. Vinay

Authors
  1. M. E. Sunil
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  2. S. Vinay
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Editor information

Editors and Affiliations

  1. Institute of Engineering, Tribhuvan University, Pulchowk Campus, Lalitpur, Nepal

    Subarna Shakya

  2. Intelligent Systems Research Centre, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Songkla University, Songkhla, Thailand

    Sinchai Kamolphiwong

  4. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

    Ke-Lin Du

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Cite this paper

Sunil, M.E., Vinay, S. (2022). Kannada Sentiment Analysis Using Vectorization and Machine Learning. In: Shakya, S., Balas, V.E., Kamolphiwong, S., Du, KL. (eds) Sentimental Analysis and Deep Learning. Advances in Intelligent Systems and Computing, vol 1408. Springer, Singapore. https://doi.org/10.1007/978-981-16-5157-1_53

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