Dataset Card for Bilingual Corpus of Arabic-English Parallel Tweets

Dataset Summary

Twitter users often post parallel tweets—tweets that contain the same content but are written in different languages. Parallel tweets can be an important resource for developing machine translation (MT) systems among other natural language processing (NLP) tasks. This resource is a result of a generic method for collecting parallel tweets. Using the method, we compiled a bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts who post English-Arabic tweets regularly. Additionally, we annotate a subset of Twitter accounts with their countries of origin and topic of interest, which provides insights about the population who post parallel tweets.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

parallelTweets:

{
  "ArabicTweetID": 981111245209243600,
  "EnglishTweetID": 981111450432401400
}

accountList:

{
  'account': 'HukoomiQatar'
}

countryTopicAnnotation:

{
  'account': 'HukoomiQatar',
  'country': 'QA',
  'topic': 'Gov'
}

Data Fields

parallelTweets:

• ArabicTweetID (int)
• EnglishTweetID (int)

accountList:

• account (str)

countryTopicAnnotation:

• account (str)
• country (class label): One of:
  • "QA",
  • "BH",
  • "AE",
  • "OM",
  • "SA",
  • "PL",
  • "JO",
  • "IQ",
  • "Other",
  • "EG",
  • "KW",
  • "SY"
• topic (class label): One of:
  • "Gov",
  • "Culture",
  • "Education",
  • "Sports",
  • "Travel",
  • "Events",
  • "Business",
  • "Science",
  • "Politics",
  • "Health",
  • "Governoment",
  • "Media",

Data Splits

All configuration have only one split: "test".

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

It is licensed under the Apache License, Version 2.0.

Citation Information

@inproceedings{Mubarak2020bilingualtweets,
  title={Constructing a Bilingual Corpus of Parallel Tweets},
  author={Mubarak, Hamdy and Hassan, Sabit and Abdelali, Ahmed},
  booktitle={Proceedings of 13th Workshop on Building and Using Comparable Corpora (BUCC)},
  address={Marseille, France},
  year={2020}
}

[More Information Needed]

Contributions

Thanks to @sumanthd17 for adding this dataset.