
# 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.
task_categories:text-classification task_ids:text-scoring annotations_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:cc-by-4.0 social-media-shares-prediction arxiv:1801.07055 region:us
{"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"], "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}}
TAGS
#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #social-media-shares-prediction #arxiv-1801.07055 #region-us 


# Dataset Card for News Popularity in Multiple Social Media Platforms

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## 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



### 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



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information

License: Creative Commons Attribution 4.0 International License (CC-BY)





### Contributions

Thanks to @frankier for adding this dataset.
# Dataset Card for News Popularity in Multiple Social Media Platforms ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## 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 ### 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 ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

License: Creative Commons Attribution 4.0 International License (CC-BY) ### Contributions

Thanks to @frankier for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #social-media-shares-prediction #arxiv-1801.07055 #region-us 
 # Dataset Card for News Popularity in Multiple Social Media Platforms ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## 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 ### 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 ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

License: Creative Commons Attribution 4.0 International License (CC-BY) ### Contributions

Thanks to @frankier for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-text-scoring #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #social-media-shares-prediction #arxiv-1801.07055 #region-us 
# Dataset Card for News Popularity in Multiple Social Media Platforms## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## 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### 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