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README.md
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- text-classification
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# AutoTrain Dataset for project: github-emotion-
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## Dataset Description
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Dataset used in the paper: Imran et al., ["Data Augmentation for Improving Emotion Recognition in Software Engineering Communication"](https://arxiv.org/abs/2208.05573), ASE-2022.
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The BCP-47 code for the dataset's language is unk.
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## Dataset Structure
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A sample from this dataset looks as follows:
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```json
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[
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{
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"feat_id": 704844644,
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"text": "This change doesn't affect anything but makes the code more clear. If you look at the line about, `currentUrlTree` is set to `urlAfterRedirects`.",
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"feat_Anger": 0,
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"feat_Love": 0,
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"feat_Fear": 0,
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"feat_Joy": 1,
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"feat_Sadness": 0,
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"target": 0
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"feat_id": 886568180,
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"text": "Thanks very much for your feedback [USER] Your point is totally fair. My intention was to highlight that camelCase or dash-case class names are perfectly fine to use in Angular templates. Most people, especially beginners, do not know that and end up using the `ngClass` directive. Do you think that rewording the alert towards that direction would make sense?",
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"feat_Anger": 0,
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"feat_Love": 1,
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"feat_Fear": 0,
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"feat_Joy": 0,
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"feat_Sadness": 0,
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"target": 0
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}
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]
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```
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```json
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{
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"feat_id": "Value(dtype='int64', id=None)",
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"text": "Value(dtype='string', id=None)",
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"feat_Anger": "Value(dtype='int64', id=None)",
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"feat_Love": "Value(dtype='int64', id=None)",
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"feat_Fear": "Value(dtype='int64', id=None)",
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"feat_Joy": "Value(dtype='int64', id=None)",
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"feat_Sadness": "Value(dtype='int64', id=None)",
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"target": "ClassLabel(num_classes=2, names=['0', '1'], id=None)"
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}
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```
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### Dataset Splits
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This dataset is split into a train and
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| Split name | Num samples |
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| ------------ | ------------------- |
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| train | 1600 |
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# AutoTrain Dataset for project: github-emotion-love
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## Dataset Description
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Dataset used in the paper: Imran et al., ["Data Augmentation for Improving Emotion Recognition in Software Engineering Communication"](https://arxiv.org/abs/2208.05573), ASE-2022.
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This is an annotated dataset of 2000 GitHub comments. Six basic emotions are annotated. They are Anger, Love, Fear, Joy, Sadness and Surprise. This repository contains annotations of all emotions.
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## Dataset Structure
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Dataset is in CSV format. The columns are:
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```id, modified_comment, Anger, Love, Fear, Joy, Sadness, Surprise```
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Here, `id` is a unique id for each comment. Each emotion is marked as 1 or 0.
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### Dataset Splits
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This dataset is split into a train and test split. The split sizes are as follows:
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| Split name | Num samples |
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| ------------ | ------------------- |
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| train | 1600 |
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| test | 400 |
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