metadata

license: cc-by-4.0
language:
  - es
  - en
  - de
  - ar
  - pt
  - fr
  - nl
  - it
  - hi
size_categories:
  - 10K<n<100K

Dataset Summary

MultiPICo (Multilingual Perspectivist Irony Corpus) is a disaggregated multilingual corpus for irony detection, containing 18,778 pairs of short conversations (post-reply) from Twitter (8,956) and Reddit (9,822), along with the demographic information of each annotator (age, nationality, gender, and so on).

Supported Tasks and Leaderboards

Irony classification task using soft labels (i.e., distribution of annotations) or hard labels (i.e., aggregated labels).

Languages

MultiPICo is a multilingual corpus containing texts in different varieties of each language (see column "language_variety")

Data Instances

Spanish: 4,683 instances and 122 annotators
English: 2,999 instances and 74 annotators
German: 2,375 instances and 70 annotators
Arabic: 2,181 instances and 68 annotators
Portuguese: 1,994 instances and 49 annotators
French: 1,760 instances and 50 annotators
Dutch: 1,000 instances and 25 annotators
Italian: 1,000 instances and 24 annotators
Hindi: 786 instances and 24 annotators

Total amount of instances: 94,342

Total number of annotators: 506

Data Fields

MultiPICo is structured as follows:

in rows, the annotation of each annotator (identified with a “annotator_id”)
in columns, the various information about the target text annotated by the user (post_id, post, reply_id, reply, language, and language_variety), and the metadata about annotators (age, self-identified gender, ethnicity, and so on).

Data Splits

The corpus is not split in training and validation/test sets.

Initial Data Collection and Normalization

Information about the creation of MultiPICo are available in the paper.

Who are the source language producers?

Reddit and Twitter users.

Annotation process

The annotation process has been performed on Prolific platform.

Who are the annotators?

The annotators are native speakers coming from different countries.

Personal and Sensitive Information

All the personal information available about the annotators in MultiPICo are provided by Prolific platform and under their consensus. In the corpus, any metadata about the user who generated the texts on Reddit and Twitter are not available.

Social Impact of Dataset

MultiPICo has not a specific social impact, but the proposition of datasets released with disaggregated annotations is encouraging the community to develop more inclusive, and thus respectful of various perspectives, AI-based technologies.

Discussion of Biases

The analysis proposed in our work shows that in case of aggregation of labels employing a majority voting strategy, some biases can be introduced in the dataset. However, we release the dataset in its disaggregated form, and for its annotation we took into account various annotators with different sociodemographic traits.

Other Known Limitations

About the self-identified gender dimension, we are aware of the wider spectrum of genders. However, this information is provided by the annotators only in a binary form. Another potential limitation is that, in the spirit of constructing a perspectivist corpus, we fully trusted the contributors. While the chosen crowdsourcing platform (Prolific) is known for a high quality standard obtained, and we added a layer of checks through attention test questions, random noise in the annotation may still be present and undetected.

Dataset Curators

Department of Computer Science at the University of Turin.

Citation Information

@inproceedings{multipico,
  title = {{M}ulti{PIC}o: 
{M}ultilingual {P}erspectivist {I}rony {C}orpus},
  booktitle = {Proceedings of the 62th {{Annual Meeting}} of the {{Association}} for {{Computational Linguistics}}},
  author = {Casola, Silvia and Frenda, Simona and Lo, Soda Marem and Sezerer, Erhan and Uva, Antonio and Basile, Valerio and Bosco, Cristina and Pedrani, Alessandro and Rubagotti, Chiara and Patti, Viviana and Bernardi, Davide},
  year = {2024},
  month = aug,
  publisher = {Association for Computational Linguistics},
  address = {Online},
}

Contributions

The creation of this dataset was partially funded by the Multilingual Perspective-Aware NLU project in partnership with Amazon Alexa.