Datasets:
QCRI
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Modalities:
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Formats:
json
Languages:
English
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Firoj's picture
updated readme
9f5c584
metadata
license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - Disaster Informatics
  - Crisis Informatics
  - Social Media
pretty_name: >-
  CrisisBench: Benchmarking Crisis-related Social Media Datasets for
  Humanitarian Information Processing -- Multiple Languages Dataset
size_categories:
  - 10K<n<100K
dataset_info:
  - config_name: informativeness
    splits:
      - name: train
        num_examples: 116268
      - name: dev
        num_examples: 16942
      - name: test
        num_examples: 32888
  - config_name: humanitarian
    splits:
      - name: train
        num_examples: 99073
      - name: dev
        num_examples: 14436
      - name: test
        num_examples: 28024
configs:
  - config_name: informativeness
    data_files:
      - split: test
        path: informativeness/test.json
      - split: dev
        path: informativeness/dev.json
      - split: train
        path: informativeness/train.json
  - config_name: humanitarian
    data_files:
      - split: test
        path: humanitarian/test.json
      - split: dev
        path: humanitarian/dev.json
      - split: train
        path: humanitarian/train.json

CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing

The crisis benchmark dataset consists of data from several different sources, such as CrisisLex (CrisisLex26, CrisisLex6), CrisisNLP, SWDM2013, ISCRAM13, Disaster Response Data (DRD), Disasters on Social Media (DSM), CrisisMMD, and data from AIDR.

The purpose of this work was to map the class labels, remove duplicates, and provide benchmark results for the community.

Dataset

This is the set with multiple languages of the whole CrisisBench dataset. Please check the CrisisBench Collection

Data format

Each JSON object contains the following fields:

  • id: Corresponds to the user tweet ID from Twitter.
  • event: Event name associated with the respective dataset.
  • source: Source of the dataset.
  • text: Tweet text.
  • lang: Language tag obtained either from Twitter or from the Google Language Detection API.
  • lang_conf: Confidence score obtained from the Google Language Detection API. In some cases, the tag is marked as "NA," indicating that the language tag was obtained from Twitter rather than the API.
  • class_label: Class label assigned to a given tweet text.

Downloads (Alternate Links)

Labeled data and other resources

Experimental Scripts:

Source code to run the experiments is available at https://github.com/firojalam/crisis_datasets_benchmarks

License

This version of the dataset is distributed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). The full license text can be found in the accompanying licenses_by-nc-sa_4.0_legalcode.txt file.

Citation

If you use this data in your research, please consider citing the following paper:

[1] Firoj Alam, Hassan Sajjad, Muhammad Imran and Ferda Ofli, CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing, In ICWSM, 2021. Paper

@inproceedings{firojalamcrisisbenchmark2020,
Author = {Firoj Alam, Hassan Sajjad, Muhammad Imran, Ferda Ofli},
Keywords = {Social Media, Crisis Computing, Tweet Text Classification, Disaster Response},
Booktitle = {15th International Conference on Web and Social Media (ICWSM)},
Title = {{CrisisBench:} Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing},
Year = {2021}
}
  • and the following associated papers

  • Muhammad Imran, Prasenjit Mitra, Carlos Castillo. Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages. In Proceedings of the 10th Language Resources and Evaluation Conference (LREC), 2016, Slovenia.

  • A. Olteanu, S. Vieweg, C. Castillo. 2015. What to Expect When the Unexpected Happens: Social Media Communications Across Crises. In Proceedings of the ACM 2015 Conference on Computer Supported Cooperative Work and Social Computing (CSCW '15). ACM, Vancouver, BC, Canada.

  • A. Olteanu, C. Castillo, F. Diaz, S. Vieweg. 2014. CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises. In Proceedings of the AAAI Conference on Weblogs and Social Media (ICWSM'14). AAAI Press, Ann Arbor, MI, USA.

  • Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Diaz and Patrick Meier. Practical Extraction of Disaster-Relevant Information from Social Media. In Social Web for Disaster Management (SWDM'13) - Co-located with WWW, May 2013, Rio de Janeiro, Brazil.

  • Muhammad Imran, Shady Elbassuoni, Carlos Castillo, Fernando Diaz and Patrick Meier. Extracting Information Nuggets from Disaster-Related Messages in Social Media. In Proceedings of the 10th International Conference on Information Systems for Crisis Response and Management (ISCRAM), May 2013, Baden-Baden, Germany.

@inproceedings{imran2016lrec,
  author = {Muhammad Imran and Prasenjit Mitra and Carlos Castillo},
  title = {Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages},
  booktitle = {Proc. of the LREC, 2016},
  year = {2016},
  month = {5},
  publisher = {ELRA},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
 @inproceedings{olteanu2015expect,
  title={What to expect when the unexpected happens: Social media communications across crises},
  author={Olteanu, Alexandra and Vieweg, Sarah and Castillo, Carlos},
  booktitle={Proc. of the 18th ACM Conference on Computer Supported Cooperative Work \& Social Computing},
  pages={994--1009},
  year={2015},
  organization={ACM}
}
@inproceedings{olteanu2014crisislex,
  title={CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises.},
  author={Olteanu, Alexandra and Castillo, Carlos and Diaz, Fernando and Vieweg, Sarah},
  booktitle = "Proc. of the 8th ICWSM, 2014",
  publisher = "AAAI press",
  year={2014}
}
@inproceedings{imran2013practical,
  title={Practical extraction of disaster-relevant information from social media},
  author={Imran, Muhammad and Elbassuoni, Shady and Castillo, Carlos and Diaz, Fernando and Meier, Patrick},
  booktitle={Proc. of the 22nd WWW},
  pages={1021--1024},
  year={2013},
  organization={ACM}
}
@inproceedings{imran2013extracting,
  title={Extracting information nuggets from disaster-related messages in social media},
  author={Imran, Muhammad and Elbassuoni, Shady Mamoon and Castillo, Carlos and Diaz, Fernando and Meier, Patrick},
  booktitle={Proc. of the 12th ISCRAM},
  year={2013}
}