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metadata
annotations_creators:
  - expert-generated
language_creators:
  - crowdsourced
language:
  - en
  - kn
language_bcp47:
  - en-IN
  - kn-IN
license:
  - cc-by-4.0
multilinguality:
  - multilingual
pretty_name: KanHope
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - multi-label-classification
tags:
  - hope-speech-detection

Dataset Card for KanHope

Table of Contents

Dataset Description

Dataset Summary

KanHope dataset is a code-mixed Kannada-English dataset for hope speech detection. All texts are scraped from the comments section of YouTube. The dataset consists of 6,176 user-generated comments in code mixed Kannada scraped from YouTube and manually annotated as bearing hope speech or Not-hope speech.

Supported Tasks and Leaderboards

This task aims to detect Hope speech content of the code-mixed dataset of comments/posts in Dravidian Languages ( Kannada-English) collected from social media. The comment/post may contain more than one sentence, but the average sentence length of the corpora is 1. Each comment/post is annotated at the comment/post level. This dataset also has class imbalance problems depicting real-world scenarios.

Languages

Code-mixed text in Dravidian languages (Kannada-English).

Dataset Structure

Data Instances

An example from the Kannada dataset looks as follows:

text label
��������� ��ͭ� heartly heltidini... plz avrigella namma nimmellara supprt beku 0 (Non_hope speech)
Next song gu kuda alru andre evaga yar comment madidera alla alrru like madi share madi nam industry na next level ge togond hogaona. 1 (Hope Speech)

Data Fields

Kannada

  • text: Kannada-English code mixed comment.
  • label: integer from either of 0 or 1 that corresponds to these values: "Non_hope Speech", "Hope Speech"

Data Splits

train validation test
Kannada 4941 618 617

Dataset Creation

Curation Rationale

Numerous methods have been developed to monitor the spread of negativity in modern years by eliminating vulgar, offensive, and fierce comments from social media platforms. However, there are relatively lesser amounts of study that converges on embracing positivity, reinforcing supportive and reassuring content in online forums.

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

Youtube users

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

[Needs More Information]

Citation Information

@misc{hande2021hope,
      title={Hope Speech detection in under-resourced Kannada language}, 
      author={Adeep Hande and Ruba Priyadharshini and Anbukkarasi Sampath and Kingston Pal Thamburaj and Prabakaran Chandran and Bharathi Raja Chakravarthi},
      year={2021},
      eprint={2108.04616},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Contributions

Thanks to @adeepH for adding this dataset.