dengue_filipino / README.md
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metadata
annotations_creators:
  - crowdsourced
  - machine-generated
language_creators:
  - crowdsourced
language:
  - tl
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - multi-class-classification
paperswithcode_id: dengue
pretty_name: Dengue Dataset in Filipino
dataset_info:
  features:
    - name: text
      dtype: string
    - name: absent
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '1'
    - name: dengue
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '1'
    - name: health
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '1'
    - name: mosquito
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '1'
    - name: sick
      dtype:
        class_label:
          names:
            '0': '0'
            '1': '1'
  splits:
    - name: train
      num_bytes: 428553
      num_examples: 4015
    - name: test
      num_bytes: 428553
      num_examples: 4015
    - name: validation
      num_bytes: 54384
      num_examples: 500
  download_size: 156014
  dataset_size: 911490

Dataset Card for Dengue Dataset in Filipino

Table of Contents

Dataset Description

Dataset Summary

Benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The dataset is primarily in Filipino, with the addition of some English words commonly used in Filipino vernacular.

Dataset Structure

Data Instances

Sample data:

{
  "text": "Tapos ang dami pang lamok.",
  "absent": "0",
  "dengue": "0",
  "health": "0",
  "mosquito": "1",
  "sick": "0"
}

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

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

Jan Christian Cruz

Licensing Information

[More Information Needed]

Citation Information

@INPROCEEDINGS{8459963, author={E. D. {Livelo} and C. {Cheng}}, booktitle={2018 IEEE International Conference on Agents (ICA)}, title={Intelligent Dengue Infoveillance Using Gated Recurrent Neural Learning and Cross-Label Frequencies}, year={2018}, volume={}, number={}, pages={2-7}, doi={10.1109/AGENTS.2018.8459963}} }

Contributions

Thanks to @anaerobeth for adding this dataset.