Datasets:
Tasks:
Text Classification
Sub-tasks:
text-scoring
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - text-scoring | |
| paperswithcode_id: null | |
| pretty_name: News Popularity in Multiple Social Media Platforms | |
| tags: | |
| - social-media-shares-prediction | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: int32 | |
| - name: title | |
| dtype: string | |
| - name: headline | |
| dtype: string | |
| - name: source | |
| dtype: string | |
| - name: topic | |
| dtype: string | |
| - name: publish_date | |
| dtype: string | |
| - name: facebook | |
| dtype: int32 | |
| - name: google_plus | |
| dtype: int32 | |
| - name: linked_in | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 27927641 | |
| num_examples: 93239 | |
| download_size: 30338277 | |
| dataset_size: 27927641 | |
| # Dataset Card for News Popularity in Multiple Social Media Platforms | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [UCI](https://archive.ics.uci.edu/ml/datasets/News+Popularity+in+Multiple+Social+Media+Platforms) | |
| - **Repository:** | |
| - **Paper:** [Arxiv](https://arxiv.org/abs/1801.07055) | |
| - **Leaderboard:** [Kaggle](https://www.kaggle.com/nikhiljohnk/news-popularity-in-multiple-social-media-platforms/code) | |
| - **Point of Contact:** | |
| ### Dataset Summary | |
| Social sharing data across Facebook, Google+ and LinkedIn for 100k news items on the topics of: economy, microsoft, obama and palestine. | |
| ### Supported Tasks and Leaderboards | |
| Popularity prediction/shares prediction | |
| ### Languages | |
| English | |
| ## Dataset Structure | |
| ### Data Instances | |
| ``` | |
| { "id": 35873, | |
| "title": "Microsoft's 'teen girl' AI turns into a Hitler-loving sex robot within 24 ...", | |
| "headline": "Developers at Microsoft created 'Tay', an AI modelled to speak 'like a teen girl', in order to improve the customer service on their voice", | |
| "source": "Telegraph.co.uk", | |
| "topic": "microsoft", | |
| "publish_date": "2016-03-24 09:53:54", | |
| "facebook": 22346, | |
| "google_plus": 973, | |
| "linked_in": 1009 | |
| } | |
| ``` | |
| ### Data Fields | |
| - id: the sentence id in the source dataset | |
| - title: the title of the link as shared on social media | |
| - headline: the headline, or sometimes the lede of the story | |
| - source: the source news site | |
| - topic: the topic: one of "economy", "microsoft", "obama" and "palestine" | |
| - publish_date: the date the original article was published | |
| - facebook: the number of Facebook shares, or -1 if this data wasn't collected | |
| - google_plus: the number of Google+ likes, or -1 if this data wasn't collected | |
| - linked_in: the number of LinkedIn shares, or -1 if if this data wasn't collected | |
| ### Data Splits | |
| None | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| #### Who are the source language producers? | |
| The source headlines were by journalists, while the titles were written by the | |
| people sharing it on social media. | |
| ### Annotations | |
| #### Annotation process | |
| The 'annotations' are simply the number of shares, or likes in the case of | |
| Google+ as collected from various API endpoints. | |
| #### Who are the annotators? | |
| Social media users. | |
| ### 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 | |
| [More Information Needed] | |
| ### Licensing Information | |
| License: Creative Commons Attribution 4.0 International License (CC-BY) | |
| ### Citation Information | |
| ``` | |
| @article{Moniz2018MultiSourceSF, | |
| title={Multi-Source Social Feedback of Online News Feeds}, | |
| author={N. Moniz and L. Torgo}, | |
| journal={ArXiv}, | |
| year={2018}, | |
| volume={abs/1801.07055} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@frankier](https://github.com/frankier) for adding this dataset. |