227 lines
9.7 KiB
TypeScript
227 lines
9.7 KiB
TypeScript
import type { Meta, StoryObj } from '@storybook/react';
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import { Catalog } from '../src/components/Catalog';
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// More on how to set up stories at: https://storybook.js.org/docs/react/writing-stories/introduction
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const meta: Meta = {
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title: 'Components/Catalog',
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component: Catalog,
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tags: ['autodocs'],
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argTypes: {
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datasets: {
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description:
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'Lists of datasets to be displayed in the list, will usually be automatically available',
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},
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facets: {
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description:
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'List of frontmatter fields that should be used as filters, needs to match exactly with the field name',
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},
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},
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};
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export default meta;
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type Story = StoryObj<{ datasets: any; facets: string[] }>;
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// More on writing stories with args: https://storybook.js.org/docs/react/writing-stories/args
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export const WithoutFacets: Story = {
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name: 'Catalog without facets',
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args: {
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datasets: [
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{
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_id: '07026b22d49916754df1dc8ffb9ccd1c31878aae',
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url_path: 'dataset-4',
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file_path: 'content/dataset-4/index.md',
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metadata: {
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title: 'Detecting Abusive Albanian',
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'link-to-publication': 'https://arxiv.org/abs/2107.13592',
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'link-to-data': 'https://doi.org/10.6084/m9.figshare.19333298.v1',
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'task-description':
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'Hierarchical (offensive/not; untargeted/targeted; person/group/other)',
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'details-of-task':
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'Detect and categorise abusive language in social media data',
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'size-of-dataset': 11874,
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'percentage-abusive': 13.2,
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language: 'Albanian',
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'level-of-annotation': ['Posts'],
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platform: ['Instagram', 'Youtube'],
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medium: ['Text'],
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reference:
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'Nurce, E., Keci, J., Derczynski, L., 2021. Detecting Abusive Albanian. arXiv:2107.13592',
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},
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},
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{
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_id: '42c86cf3c4fbbab11d91c2a7d6dcb8f750bc4e19',
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url_path: 'dataset-1',
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file_path: 'content/dataset-1/index.md',
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metadata: {
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title: 'AbuseEval v1.0',
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'link-to-publication':
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'http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.760.pdf',
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'link-to-data': 'https://github.com/tommasoc80/AbuseEval',
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'task-description':
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'Explicitness annotation of offensive and abusive content',
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'details-of-task':
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'Enriched versions of the OffensEval/OLID dataset with the distinction of explicit/implicit offensive messages and the new dimension for abusive messages. Labels for offensive language: EXPLICIT, IMPLICT, NOT; Labels for abusive language: EXPLICIT, IMPLICT, NOTABU',
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'size-of-dataset': 14100,
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'percentage-abusive': 20.75,
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language: 'English',
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'level-of-annotation': ['Tweets'],
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platform: ['Twitter'],
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medium: ['Text'],
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reference:
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'Caselli, T., Basile, V., Jelena, M., Inga, K., and Michael, G. 2020. "I feel offended, don’t be abusive! implicit/explicit messages in offensive and abusive language". The 12th Language Resources and Evaluation Conference (pp. 6193-6202). European Language Resources Association.',
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},
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},
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{
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_id: '80001dd32a752421fdcc64e91fbd237dc31d6bb3',
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url_path: 'dataset-2',
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file_path: 'content/dataset-2/index.md',
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metadata: {
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title:
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'Abusive Language Detection on Arabic Social Media (Al Jazeera)',
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'link-to-publication': 'https://www.aclweb.org/anthology/W17-3008',
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'link-to-data':
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'http://alt.qcri.org/~hmubarak/offensive/AJCommentsClassification-CF.xlsx',
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'task-description':
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'Ternary (Obscene, Offensive but not obscene, Clean)',
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'details-of-task': 'Incivility',
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'size-of-dataset': 32000,
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'percentage-abusive': 0.81,
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language: 'Arabic',
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'level-of-annotation': ['Posts'],
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platform: ['AlJazeera'],
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medium: ['Text'],
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reference:
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'Mubarak, H., Darwish, K. and Magdy, W., 2017. Abusive Language Detection on Arabic Social Media. In: Proceedings of the First Workshop on Abusive Language Online. Vancouver, Canada: Association for Computational Linguistics, pp.52-56.',
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},
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},
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{
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_id: '96649d05d8193f4333b10015af76c6562971bd8c',
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url_path: 'dataset-3',
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file_path: 'content/dataset-3/index.md',
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metadata: {
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title: 'CoRAL: a Context-aware Croatian Abusive Language Dataset',
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'link-to-publication':
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'https://aclanthology.org/2022.findings-aacl.21/',
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'link-to-data':
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'https://github.com/shekharRavi/CoRAL-dataset-Findings-of-the-ACL-AACL-IJCNLP-2022',
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'task-description':
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'Multi-class based on context dependency categories (CDC)',
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'details-of-task': 'Detectioning CDC from abusive comments',
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'size-of-dataset': 2240,
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'percentage-abusive': 100,
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language: 'Croatian',
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'level-of-annotation': ['Posts'],
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platform: ['Posts'],
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medium: ['Newspaper Comments'],
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reference:
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'Ravi Shekhar, Mladen Karan and Matthew Purver (2022). CoRAL: a Context-aware Croatian Abusive Language Dataset. Findings of the ACL: AACL-IJCNLP.',
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},
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},
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],
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},
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};
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;
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export const WithFacets: Story = {
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name: 'Catalog with facets',
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args: {
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datasets: [
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{
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_id: '07026b22d49916754df1dc8ffb9ccd1c31878aae',
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url_path: 'dataset-4',
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file_path: 'content/dataset-4/index.md',
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metadata: {
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title: 'Detecting Abusive Albanian',
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'link-to-publication': 'https://arxiv.org/abs/2107.13592',
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'link-to-data': 'https://doi.org/10.6084/m9.figshare.19333298.v1',
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'task-description':
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'Hierarchical (offensive/not; untargeted/targeted; person/group/other)',
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'details-of-task':
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'Detect and categorise abusive language in social media data',
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'size-of-dataset': 11874,
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'percentage-abusive': 13.2,
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language: 'Albanian',
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'level-of-annotation': ['Posts'],
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platform: ['Instagram', 'Youtube'],
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medium: ['Text'],
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reference:
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'Nurce, E., Keci, J., Derczynski, L., 2021. Detecting Abusive Albanian. arXiv:2107.13592',
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},
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},
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{
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_id: '42c86cf3c4fbbab11d91c2a7d6dcb8f750bc4e19',
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url_path: 'dataset-1',
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file_path: 'content/dataset-1/index.md',
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metadata: {
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title: 'AbuseEval v1.0',
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'link-to-publication':
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'http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.760.pdf',
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'link-to-data': 'https://github.com/tommasoc80/AbuseEval',
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'task-description':
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'Explicitness annotation of offensive and abusive content',
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'details-of-task':
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'Enriched versions of the OffensEval/OLID dataset with the distinction of explicit/implicit offensive messages and the new dimension for abusive messages. Labels for offensive language: EXPLICIT, IMPLICT, NOT; Labels for abusive language: EXPLICIT, IMPLICT, NOTABU',
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'size-of-dataset': 14100,
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'percentage-abusive': 20.75,
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language: 'English',
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'level-of-annotation': ['Tweets'],
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platform: ['Twitter'],
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medium: ['Text'],
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reference:
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'Caselli, T., Basile, V., Jelena, M., Inga, K., and Michael, G. 2020. "I feel offended, don’t be abusive! implicit/explicit messages in offensive and abusive language". The 12th Language Resources and Evaluation Conference (pp. 6193-6202). European Language Resources Association.',
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},
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},
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{
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_id: '80001dd32a752421fdcc64e91fbd237dc31d6bb3',
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url_path: 'dataset-2',
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file_path: 'content/dataset-2/index.md',
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metadata: {
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title:
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'Abusive Language Detection on Arabic Social Media (Al Jazeera)',
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'link-to-publication': 'https://www.aclweb.org/anthology/W17-3008',
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'link-to-data':
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'http://alt.qcri.org/~hmubarak/offensive/AJCommentsClassification-CF.xlsx',
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'task-description':
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'Ternary (Obscene, Offensive but not obscene, Clean)',
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'details-of-task': 'Incivility',
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'size-of-dataset': 32000,
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'percentage-abusive': 0.81,
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language: 'Arabic',
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'level-of-annotation': ['Posts'],
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platform: ['AlJazeera'],
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medium: ['Text'],
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reference:
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'Mubarak, H., Darwish, K. and Magdy, W., 2017. Abusive Language Detection on Arabic Social Media. In: Proceedings of the First Workshop on Abusive Language Online. Vancouver, Canada: Association for Computational Linguistics, pp.52-56.',
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},
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},
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{
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_id: '96649d05d8193f4333b10015af76c6562971bd8c',
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url_path: 'dataset-3',
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file_path: 'content/dataset-3/index.md',
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metadata: {
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title: 'CoRAL: a Context-aware Croatian Abusive Language Dataset',
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'link-to-publication':
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'https://aclanthology.org/2022.findings-aacl.21/',
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'link-to-data':
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'https://github.com/shekharRavi/CoRAL-dataset-Findings-of-the-ACL-AACL-IJCNLP-2022',
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'task-description':
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'Multi-class based on context dependency categories (CDC)',
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'details-of-task': 'Detectioning CDC from abusive comments',
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'size-of-dataset': 2240,
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'percentage-abusive': 100,
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language: 'Croatian',
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'level-of-annotation': ['Posts'],
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platform: ['Posts'],
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medium: ['Newspaper Comments'],
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reference:
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'Ravi Shekhar, Mladen Karan and Matthew Purver (2022). CoRAL: a Context-aware Croatian Abusive Language Dataset. Findings of the ACL: AACL-IJCNLP.',
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},
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},
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],
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facets: ['language', 'platform']
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},
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};
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;
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