README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - en
  - fi
license:
  - cc-by-4.0
multilinguality:
  - multilingual
size_categories:
  - 10K<n<100K
  - 1K<n<10K
source_datasets:
  - extended|other-OpenSubtitles2016
task_categories:
  - text-classification
task_ids:
  - intent-classification
  - multi-class-classification
  - multi-label-classification
  - sentiment-classification
paperswithcode_id: xed
pretty_name: XedEnglishFinnish
dataset_info:
  - config_name: en_annotated
    features:
      - name: sentence
        dtype: string
      - name: labels
        sequence:
          class_label:
            names:
              '0': neutral
              '1': anger
              '2': anticipation
              '3': disgust
              '4': fear
              '5': joy
              '6': sadness
              '7': surprise
              '8': trust
    splits:
      - name: train
        num_bytes: 1018485
        num_examples: 17528
    download_size: 2421235
    dataset_size: 1018485
  - config_name: en_neutral
    features:
      - name: sentence
        dtype: string
      - name: labels
        dtype:
          class_label:
            names:
              '0': neutral
              '1': anger
              '2': anticipation
              '3': disgust
              '4': fear
              '5': joy
              '6': sadness
              '7': surprise
              '8': trust
    splits:
      - name: train
        num_bytes: 401129
        num_examples: 9675
    download_size: 2421235
    dataset_size: 401129
  - config_name: fi_annotated
    features:
      - name: sentence
        dtype: string
      - name: labels
        sequence:
          class_label:
            names:
              '0': neutral
              '1': anger
              '2': anticipation
              '3': disgust
              '4': fear
              '5': joy
              '6': sadness
              '7': surprise
              '8': trust
    splits:
      - name: train
        num_bytes: 756224
        num_examples: 14449
    download_size: 2421235
    dataset_size: 756224
  - config_name: fi_neutral
    features:
      - name: sentence
        dtype: string
      - name: labels
        dtype:
          class_label:
            names:
              '0': neutral
              '1': anger
              '2': anticipation
              '3': disgust
              '4': fear
              '5': joy
              '6': sadness
              '7': surprise
              '8': trust
    splits:
      - name: train
        num_bytes: 427499
        num_examples: 10794
    download_size: 2421235
    dataset_size: 427499
config_names:
  - en_annotated
  - en_neutral
  - fi_annotated
  - fi_neutral

Dataset Card for xed_english_finnish

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage:
• Repository: Github
• Paper: Arxiv
• Leaderboard:
• Point of Contact:

Dataset Summary

This is the XED dataset. The dataset consists of emotion annotated movie subtitles from OPUS. We use Plutchik's 8 core emotions to annotate. The data is multilabel. The original annotations have been sourced for mainly English and Finnish. For the English data we used Stanford NER (named entity recognition) (Finkel et al., 2005) to replace names and locations with the tags: [PERSON] and [LOCATION] respectively. For the Finnish data, we replaced names and locations using the Turku NER corpus (Luoma et al., 2020).

Supported Tasks and Leaderboards

Sentiment Classification, Multilabel Classification, Multilabel Classification, Intent Classification

Languages

English, Finnish

Dataset Structure

Data Instances

{ "sentence": "A confession that you hired [PERSON] ... and are responsible for my father's murder."
   "labels": [1, 6]  # anger, sadness
}

Data Fields

• sentence: a line from the dataset
• labels: labels corresponding to the emotion as an integer

Where the number indicates the emotion in ascending alphabetical order: anger:1, anticipation:2, disgust:3, fear:4, joy:5, sadness:6, surprise:7, trust:8, with neutral:0 where applicable.

Data Splits

For English: Number of unique data points: 17528 ('en_annotated' config) + 9675 ('en_neutral' config) Number of emotions: 8 (+neutral)

For Finnish: Number of unique data points: 14449 ('fi_annotated' config) + 10794 ('fi_neutral' config) Number of emotions: 8 (+neutral)

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

License: Creative Commons Attribution 4.0 International License (CC-BY)

Citation Information

@inproceedings{ohman2020xed, title={XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection}, author={{"O}hman, Emily and P{`a}mies, Marc and Kajava, Kaisla and Tiedemann, J{"o}rg}, booktitle={The 28th International Conference on Computational Linguistics (COLING 2020)}, year={2020} }

Contributions

Thanks to @lhoestq, @harshalmittal4 for adding this dataset.