Datasets:
factckbr

- {"default": {"description": "A dataset to study Fake News in Portuguese, presenting a supposedly false News along with their respective fact check and classification.\nThe data is collected from the ClaimReview, a structured data schema used by fact check agencies to share their results in search engines, enabling data collect in real time.\nThe FACTCK.BR dataset contains 1309 claims with its corresponding label.\n", "citation": "\n @inproceedings{10.1145/3323503.3361698,\n author = {Moreno, Jo\\~{a}o and Bressan, Gra\\c{c}a},\n title = {FACTCK.BR: A New Dataset to Study Fake News},\n year = {2019},\n isbn = {9781450367639},\n publisher = {Association for Computing Machinery},\n address = {New York, NY, USA},\n url = {https://doi.org/10.1145/3323503.3361698},\n doi = {10.1145/3323503.3361698},\n abstract = {Machine learning algorithms can be used to combat fake news propagation. For the news classification, labeled datasets are required, however, among the existing datasets, few separate verified false from skewed ones with a good variety of sources. This work presents FACTCK.BR, a new dataset to study Fake News in Portuguese, presenting a supposedly false News along with their respective fact check and classification. The data is collected from the ClaimReview, a structured data schema used by fact check agencies to share their results in search engines, enabling data collect in real time.},\n booktitle = {Proceedings of the 25th Brazillian Symposium on Multimedia and the Web},\n pages = {525\u2013527},\n numpages = {3},\n keywords = {fake news, fact check, information extraction, dataset},\n location = {Rio de Janeiro, Brazil},\n series = {WebMedia '19}\n}\n", "homepage": "https://github.com/jghm-f/FACTCK.BR", "license": "MIT", "features": {"url": {"dtype": "string", "id": null, "_type": "Value"}, "author": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "claim": {"dtype": "string", "id": null, "_type": "Value"}, "review": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "rating": {"dtype": "float32", "id": null, "_type": "Value"}, "best_rating": {"dtype": "float32", "id": null, "_type": "Value"}, "label": {"num_classes": 14, "names": ["falso", "distorcido", "impreciso", "exagerado", "insustent\u00e1vel", "verdadeiro", "outros", "subestimado", "imposs\u00edvel provar", "discut\u00edvel", "sem contexto", "de olho", "verdadeiro, mas", "ainda \u00e9 cedo para dizer"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "claim", "output": "label"}, "builder_name": "factckbr", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 750646, "num_examples": 1313, "dataset_name": "factckbr"}}, "download_checksums": {"https://github.com/jghm-f/FACTCK.BR/raw/master/FACTCKBR.tsv": {"num_bytes": 721314, "checksum": "1e90fe8b67af22d0f756a7f831b6a2f66072b5d0d66fb1172f3bda1e748201db"}}, "download_size": 721314, "post_processing_size": null, "dataset_size": 750646, "size_in_bytes": 1471960}}