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--- |
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language: |
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- id |
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- en |
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pretty_name: r |
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task_categories: |
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- text-classification |
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tags: |
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- product reviews |
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- sentiment |
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size_categories: |
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- 10K<n<100K |
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--- |
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## Dataset Summary |
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This dataset contains 11,606 product reviews gathered from various indonesian brands and products in several e-commerce such as Shopee, Tokopedia, Lazada, Bukalapak, Blili, and Zalora. |
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each row is marked as 1 for positive sentiment and 0 for negative sentiment. |
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This dataset has been transformed, selecting in a random way a subset of them, applying a cleaning process, and dividing them between the test and train subsets, keeping a balance between the number of positive and negative tweets within each of these subsets. |
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## Languages |
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The text in the dataset is in English and Indonesian. The 'review' column contains reviews in indonesian, and the 'translate' column contains reviews that has been translated to english |
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## Data Fields |
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In the final dataset, all files are in the JSON format with f columns: |
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| Column Name | Data | |
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| :------------ | :--------------------------------------------------------------------------------------| |
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| review | A sentence (or review) in indonesian | |
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| sentimen | The sentiment label of sentence, 1 for positive sentiment and 0 for negative sentiment| |
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| translate | A sentence (or review) in english | |
