Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
sentiment-classification
Languages:
Russian
Size:
10K - 100K
License:
Update README.md
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README.md
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@@ -18,11 +18,24 @@ Kinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).
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In total it contains 36,591 reviews from July 2004 to November 2012.
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With following distribution along the 3-point sentiment scale:
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- Good
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- Bad
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- Neutral
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```python3
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import pandas as pd
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df = pd.read_json('kinopoisk.jsonl', lines=True)
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In total it contains 36,591 reviews from July 2004 to November 2012.
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With following distribution along the 3-point sentiment scale:
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- Good: 27,264;
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- Bad: 4,751;
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- Neutral: 4,576.
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### Data Fields
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Each sample contains the following fields:
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- **part**: rank list top250 or bottom100;
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- **movie_name**;
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- **review_id**;
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- **author**: review author;
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- **date**: date of a review;
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- **title**: review title;
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- **grade3**: sentiment score Good, Bad or Neutral;
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- **grade10**: sentiment score on a 10-point scale parsed from text;
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- **content**: review text.
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### Python:
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```python3
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import pandas as pd
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df = pd.read_json('kinopoisk.jsonl', lines=True)
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