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Journals / Balkan Journal of Electrical and Computer Engineering / 2026 / Cilt: 6 Sayı: 2

A Review of Turkish Sentiment Analysis and Opinion Mining

Habibe Karayiğit
Çiğdem Acı
Ali Akdağlı
Pages
94–98
Publication Date
2018-04-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It has been tried to suggest solutions for the problems encountered in Turkish studies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Social Media is one of the most frequently used platforms today.
📊
Key Findings & Data:Users can easily share their views, ideas, and thoughts on this platform.
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Conclusion & Impact:It has been tried to suggest solutions for the problems encountered in Turkish studies.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Turkish · Sentiment Analysis · social media

Abstract

Social Media is one of the most frequently used platforms today. Users can easily share their views, ideas, and thoughts on this platform. The data shared on social media platforms is actually a great deal that can be transformed into meaningful information. The obtained big data can be analyzed and evaluated by various data analysis methods. Whether or not the data contain a feeling, if it is included; the type of the feeling (i.e. positive, negative or neutral) can be determined by emotion analysis methods. Sentiment Analysis studies in later times began to turn to analysis indicating different sentiments. Thus the foundations of Opinion Mining were laid. When ideas conveyed by social media information are presented semantically, they are expressed by Opinion Mining. The purpose of this paper is to explain the relationship between the concepts of Sentiment Analysis and Opinion Mining. The terms used in Sentiment Analysis and Opinion Mining are explained and examples of Turkish Sentiment Analysis are given. It has been tried to suggest solutions for the problems encountered in Turkish studies.

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Cite This Article

Karayiğit, H., Acı, Ç., Akdağlı, A. (2018). A Review of Turkish Sentiment Analysis and Opinion Mining. Balkan Journal of Electrical and Computer Engineering, Cilt: 6 Sayı: 2, 94–98. https://doi.org/10.17694/bajece.419547

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References (20)

  1. B. Liu, Sentiment Analysis and Opinion Mining, Morgan & Claypool Publishers, 2012
  2. S.E. Şeker, "Duygu Analizi (Sentimental Analysis)", YBS Ansiklopedi, 2016, pp.21-36
  3. B. Pang, L. Lee, S. Vaithyanathan, "Thumbs up? Sentiment Classifıcation Using Machine Leaming Techniques", Proceedings of EMNLP 2002, pp. 79-86, 2002
  4. T. Nasukawa and J. Yi, "Sentiment Analysis: Capturing favorability using natural language processing", Proceedings of the 2nd international conference on Knowledge capture, Sanibel Island, FL, USA, 2003
  5. K. Dave, S. Lawrence, and M. P. David, "Mining the peanut gallery: Opinion extraction and semantic classification of product reviews", Proceedings of the 12th international conference on World Wide Web, ACM, 2003
  6. T. Kaşıkçı, H. Gökçen, "Metin Madenciliği İle E-Ticaret Sitelerinin Belirlenmesi, Bilişim Teknolojileri Dergisi", 7(1), 2014, pp. 25-32
  7. S.E. Şeker, Sınıflandırma, 08 December 2017. [Online]. Available:
  8. T. Parlar, Feature Selection for Sentiment Analysis in Turkish Texts, Published Ph.D. Thesis, Adana, 2016
  9. E. Evirgen, Sentiment Analysis of Turkish Tweets, Published Master's Thesis, İstanbul, 2016
  10. B. Kama, Feature Based Sentiment Analysis on Informal Turkish Texts, Published Master's Thesis, Ankara, 2016
  11. S. Demirci, Sentiment Analysis on Turkish tweets, Published Master's Thesis, Ankara, 2014
  12. H. Çelik, Sentiment Analysis for Turkish Language, Published Master's Thesis, İstanbul, 2013
  13. Z. Boynukalın, Sentiment Analysis of Turkish Texts by Using Machine Learning Methods, Published Master's Thesis, Ankara, 2012
  14. İ. Yelmen, Sentiment Analysis on Turkish Social Media Data with Natural Language Processing Methods, Published Master's Thesis, İstanbul, 2016
  15. Ö. Çoban, Turkish Twitter Feelings Analysis with Text Classification Techniques, Published Master's Thesis, Erzurum, 2016
  16. B. A. Kaplan, Sentiment Analysis on Turkish Twitter Messages by Using Data Mining, Published Master's Thesis, İstanbul, 2016
  17. E. A. Yurt, Sentiment Analysis in Turkish Documents, Published Master's Thesis, İstanbul, 2015
  18. C. TÜRKMENOĞLU, Sentiment Analysis in Turkish Texts, Published Master's Thesis, İstanbul, 2015
  19. F. Akba, Assesment of Feature Selection Metrics for Sentiment Analysis: Turkish Movie Reviews, Published Master's Thesis, Ankara, 2014
  20. M. Nanğır, Classification of Emotions with Multiple Classifier Methods for Turkish Language, Published Master's Thesis, İstanbul, 2013