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+ # Details
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+ This model is used for Sentiment Analysis based on BERTurk for Turkish Language https://huggingface.co/dbmdz/bert-base-turkish-cased
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+ # Dataset
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+ We used product and movie dataset provided by a study [2] . This dataset includes
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+ movie and product reviews. The products are book, DVD, electronics, and kitchen.
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+ The movie dataset is taken from a cinema Web page (www.beyazperde.com) with
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+ 5331 positive and 5331 negative sentences. Reviews in the Web page are marked in
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+ scale from 0 to 5 by the users who made the reviews. The study considered a review
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+ sentiment positive if the rating is equal to or bigger than 4, and negative if it is less
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+ or equal to 2. They also built Turkish product review dataset from an online retailer
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+ Web page. They constructed benchmark dataset consisting of reviews regarding some
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+ products (book, DVD, etc.). Likewise, reviews are marked in the range from 1 to 5,
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+ and majority class of reviews are 5. Each category has 700 positive and 700 negative
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+ reviews in which average rating of negative reviews is 2.27 and of positive reviews
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+ is 4.5.
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+ The dataset is used by following papers
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+ 1 Yildirim, Savaş. (2020). Comparing Deep Neural Networks to Traditional Models for Sentiment Analysis in Turkish Language. 10.1007/978-981-15-1216-2_12.
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+ 2 Demirtas, Erkin and Mykola Pechenizkiy. 2013. Cross-lingual polarity detection with machine translation. In Proceedings of the Second International Workshop on Issues of Sentiment
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+ Discovery and Opinion Mining (WISDOM ’13)