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Turkish E-commerce Sentiment Dataset
Data Science and Analytics
Tags and Keywords
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"No reviews yet"
Free
About
This dataset is designed for sentiment analysis of Turkish customer reviews, providing a valuable resource for natural language processing (NLP) projects. It includes reviews primarily collected from various e-commerce platforms in Turkish. The sentiments are categorised into three distinct classes: Positive, Negative, and Neutral. Users should be aware that the dataset may contain repeated entries and occasional instances where the assigned sentiment might not perfectly align with the review's content, necessitating a preprocessing step for optimal model performance. The data is supplied as a CSV file, encoded in UTF-16, which should be considered when reading the file into projects.
Columns
- Görüş: Represents the user's review or comment, typically in Turkish.
- Durum: Indicates the sentiment status of the corresponding review. This column contains one of three categories: 'Olumlu' (Positive), 'Olumsuz' (Negative), or 'Tarafsız' (Neutral).
Distribution
The dataset is provided in a .csv file format and is encoded using UTF-16. Specific numbers for rows or records are not explicitly available, however, the sentiment distribution indicates that Positive and Negative sentiments each account for 37% of the data, while the remaining 26% is categorised as Neutral (referred to as 'Other' in some contexts).
Usage
This dataset is ideal for developing and evaluating sentiment analysis models for the Turkish language. Key applications include:
- Training multiclass classification models for sentiment prediction.
- Developing Natural Language Processing (NLP) solutions for text understanding.
- Implementing deep learning architectures, such as LSTM networks, for sentiment prediction.
- Analysing customer feedback from Turkish e-commerce stores.
Coverage
The dataset primarily covers reviews written in Turkish, suggesting its applicability to contexts within Turkey or other Turkish-speaking regions. The data was gathered from various electronic stores. There is no specific time range or demographic scope detailed for the content.
License
CC0
Who Can Use It
- Data Scientists and Machine Learning Engineers for building and fine-tuning sentiment analysis models.
- NLP Researchers and Academics studying Turkish language processing and sentiment classification.
- Businesses seeking to understand and analyse Turkish customer feedback from e-commerce platforms.
Dataset Name Suggestions
- Turkish E-commerce Sentiment Dataset
- Three-Class Turkish Review Sentiment
- Turkish Customer Review Sentiment Analysis Data
Attributes
Original Data Source: Duygu Analizi Veri Seti (Olumlu/Olumsuz/Tarafsız)Duygu Analizi Veri Seti (Olumlu/Olumsuz/Tarafsız)
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