Datasets:

Sub-tasks:
text-scoring
Languages:
English
ArXiv:
License:
newspop / README.md
lhoestq's picture
lhoestq HF staff
add dataset_info in dataset metadata
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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

  • Homepage: UCI
  • Repository:
  • Paper: Arxiv
  • Leaderboard: Kaggle
  • 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 for adding this dataset.