Datasets:
Tasks:
Text Classification
Sub-tasks:
text-scoring
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
metadata
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 Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
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 for adding this dataset.