Datasets:
Tasks:
Text Classification
Sub-tasks:
text-scoring
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
Delete legacy JSON metadata
#1
by
albertvillanova
HF staff
- opened
- dataset_infos.json +0 -1
dataset_infos.json
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{"default": {"description": "\nThis is a large data set of news items and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn.\nThe collected data relates to a period of 8 months, between November 2015 and July 2016, accounting for about 100,000 news items on four different topics: economy, microsoft, obama and palestine.\nThis data set is tailored for evaluative comparisons in predictive analytics tasks, although allowing for tasks in other research areas such as topic detection and tracking, sentiment analysis in short text, first story detection or news recommendation.\n", "citation": "@article{Moniz2018MultiSourceSF,\n title={Multi-Source Social Feedback of Online News Feeds},\n author={N. Moniz and L. Torgo},\n journal={ArXiv},\n year={2018},\n volume={abs/1801.07055}\n}\n", "homepage": "https://archive.ics.uci.edu/ml/datasets/News+Popularity+in+Multiple+Social+Media+Platforms", "license": "Creative Commons Attribution 4.0 International License (CC-BY)", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "headline": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"dtype": "string", "id": null, "_type": "Value"}, "topic": {"dtype": "string", "id": null, "_type": "Value"}, "publish_date": {"dtype": "string", "id": null, "_type": "Value"}, "facebook": {"dtype": "int32", "id": null, "_type": "Value"}, "google_plus": {"dtype": "int32", "id": null, "_type": "Value"}, "linked_in": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "newspop", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 27927641, "num_examples": 93239, "dataset_name": "newspop"}}, "download_checksums": {"https://archive.ics.uci.edu/ml/machine-learning-databases/00432/Data/News_Final.csv": {"num_bytes": 30338277, "checksum": "8e74ffa71852a87fdf38ad8a05599ff2ad75f4e30e9244b07c58f1e0e70686c9"}}, "download_size": 30338277, "post_processing_size": null, "dataset_size": 27927641, "size_in_bytes": 58265918}}
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