SEACrowd/id_clickbait

CLICK-ID数据集是一个包含印度尼西亚新闻标题的集合，这些标题收集自12个本地在线新闻出版商，包括detikNews、Fimela、Kapanlagi、Kompas、Liputan6、Okezone、Posmetro-Medan、Republika、Sindonews、Tempo、Tribunnews和Wowkeren。该数据集主要由两部分组成：(i) 46,119条原始文章数据，和(ii) 15,000条带有点击诱饵标注的样本标题。标注工作由3名标注者进行，每个标题的标注结果基于多数决定。在标注样本中，6,290条被标记为点击诱饵，8,710条为非点击诱饵。该数据集支持情感分析任务。

The CLICK-ID dataset is a collection of Indonesian news headlines that was collected from 12 local online news publishers; detikNews, Fimela, Kapanlagi, Kompas, Liputan6, Okezone, Posmetro-Medan, Republika, Sindonews, Tempo, Tribunnews, and Wowkeren. This dataset is comprised of mainly two parts; (i) 46,119 raw article data, and (ii) 15,000 clickbait annotated sample headlines. Annotation was conducted with 3 annotator examining each headline. Judgment were based only on the headline. The majority then is considered as the ground truth. In the annotated sample, our annotation shows 6,290 clickbait and 8,710 non-clickbait. The dataset supports sentiment analysis tasks.

原始信息汇总

数据集概述

数据集名称

Id Clickbait

语言

印尼语

任务类别

情感分析

数据集组成

• 46,119条原始文章数据
• 15,000条经过标注的点击诱饵标题样本

标注过程

• 每个标题由3名标注者进行标注
• 根据多数意见确定标注结果
• 标注结果中，6,290条为点击诱饵，8,710条为非点击诱饵

支持的任务

情感分析

数据集版本

• 源版本：1.0.0
• SEACrowd版本：2024.06.20

数据集许可证

Creative Commons Attribution 4.0 International

引用

@article{WILLIAM2020106231, title = "CLICK-ID: A novel dataset for Indonesian clickbait headlines", journal = "Data in Brief", volume = "32", pages = "106231", year = "2020", issn = "2352-3409", doi = "https://doi.org/10.1016/j.dib.2020.106231", url = "http://www.sciencedirect.com/science/article/pii/S2352340920311252", author = "Andika William and Yunita Sari", keywords = "Indonesian, Natural Language Processing, News articles, Clickbait, Text-classification", abstract = "News analysis is a popular task in Natural Language Processing (NLP). In particular, the problem of clickbait in news analysis has gained attention in recent years [1, 2]. However, the majority of the tasks has been focused on English news, in which there is already a rich representative resource. For other languages, such as Indonesian, there is still a lack of resource for clickbait tasks. Therefore, we introduce the CLICK-ID dataset of Indonesian news headlines extracted from 12 Indonesian online news publishers. It is comprised of 15,000 annotated headlines with clickbait and non-clickbait labels. Using the CLICK-ID dataset, we then developed an Indonesian clickbait classification model achieving favourable performance. We believe that this corpus will be useful for replicable experiments in clickbait detection or other experiments in NLP areas." }

@article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }