Araştırma Makalesi

Turkish Sentiment Analysis System via Ensemble Learning

15 Ağustos 2020
  • Saed Alqaraleh
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Turkish Sentiment Analysis System via Ensemble Learning

Abstract

Nowadays, sentiment analysis (SA) also known as opinion mining (OM) is widely used and has an impressive effect in many fields, such as marketing, politics, and even, company’s products are now adjusted based on users’ opinions. In this paper, a new efficient sentiment analysis system that supports the Turkish language has been introduced. In addition, as Turkish is an agglutinative language, which requires special processing, an efficient preprocessing model was also implemented as a part of the developed system. Several experiments using the challenging and benchmark “The Turkish movie reviews” dataset have been conducted, and it is obvious that the constructed approach can efficiently support the Turkish language and can achieve a quite good performance.

Keywords

Kaynakça

  1. Social Media Examiner, "2019 Social Media Marketing Industry Report ", 2020 [Online]. Available: https://www.socialmediaexaminer.com/social-media-marketing-industry-report-2019,[Accessed: 20.1.2020].
  2. Hussein, D. M. E. D. M. (2018). A survey on sentiment analysis challenges. Journal of King Saud University-Engineering Sciences, 30(4), 330-338.
  3. Kaur, H., & Mangat, V. (2017, February). A survey of sentiment analysis techniques. In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 921-925). IEEE.
  4. Wang, H., & Zhai, C. (2017). Generative models for sentiment analysis and opinion mining. In A practical guide to sentiment analysis (pp. 107-134). Springer, Cham.
  5. Liu, R., Shi, Y., Ji, C., & Jia, M. (2019). A Survey of Sentiment Analysis Based on Transfer Learning. IEEE Access, 7, 85401-85412.
  6. Ghorbel, H., & Jacot, D. (2011). Sentiment analysis of French movie reviews. In Advances in Distributed Agent-Based Retrieval Tools (pp. 97-108). Springer, Berlin, Heidelberg.
  7. Esuli, A., & Sebastiani, F. (2006, May). Sentiwordnet: A publicly available lexical resource for opinion mining. In LREC (Vol. 6, pp. 417-422).
  8. Eroğul, U. (2009). Sentiment analysis in Turkish (Master's thesis). Middle East Technical University, Ankara.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yazarlar

Yayımlanma Tarihi

15 Ağustos 2020

Gönderilme Tarihi

28 Haziran 2020

Kabul Tarihi

10 Ağustos 2020

Yayımlandığı Sayı

Yıl 2020

Kaynak Göster

APA
Alqaraleh, S. (2020). Turkish Sentiment Analysis System via Ensemble Learning. Avrupa Bilim ve Teknoloji Dergisi, 122-129. https://doi.org/10.31590/ejosat.779181

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