A Framework for Sentiment Analysis in Turkish: Application to Polarity Detection of Movie Reviews in Turkish

  • A. Gural Vural
  • B. Barla Cambazoglu
  • Pinar Senkul
  • Z. Ozge Tokgoz
Conference paper


In this work, we present a framework for unsupervised sentiment analysis in Turkish text documents. As part of our framework, we customize the SentiStrength sentiment analysis library by translating its lexicon to Turkish. We apply our framework to the problem of classifying the polarity of movie reviews. For performance evaluation, we use a large corpus of Turkish movie reviews obtained from a popular Turkish social media site. Although our framework is unsupervised, it is demonstrated to achieve a fairly good classification accuracy, approaching the performance of supervised polarity classification techniques.


Sentiment Analysis Input Text Negative Sentiment Movie Review Sentiment Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is supported by grant number TUBITAK-112E002, TUBITAK. We thank Umut Erogul for providing us the data.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • A. Gural Vural
    • 1
  • B. Barla Cambazoglu
    • 2
  • Pinar Senkul
    • 1
  • Z. Ozge Tokgoz
    • 1
  1. 1.Middle East Technical UniversityAnkaraTurkey
  2. 2.Yahoo! ResearchBarcelonaSpain

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