metadata

license: mit
language:
  - lv
tags:
  - food
  - image
  - classification
  - image-text relation
pretty_name: Latvian Twitter Eater Corpus - Image-text Relation Classification
size_categories:
  - n<1K

Latvian Twitter Eater Corpus - Image-text Relation Classification Test Set

The data set contains images attached to the tweets, tweet IDs, text, and a manually annotated relation class between the image and tweet text. The relation classes are similar to the ones in the paper "Categorizing and Inferring the Relationship between the Text and Image of Twitter Posts"

Relations:

0 - The image ADDS to tweet meaning and tweet text IS represented in the image
1 - The image ADDS to tweet meaning but tweet text is NOT represented in the image
2 - The image does NOT ADD to tweet meaning but tweet text IS represented in the image
3 - The image does NOT ADD to tweet meaning and tweet text is NOT represented in the image

Publications

If you use this corpus or scripts, please cite the following paper:

Matīss Rikters, Edison Marrese-Taylor, Rinalds Vīksna (2024). "Annotations for Exploring Food Tweets from Multiple Aspects." In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (2024).

@inproceedings{rikters-etal-2024-annotations-exploring,
    title = "Annotations for Exploring Food Tweets from Multiple Aspects",
    author = "Rikters, Matiss  and
      V{\=\i}ksna, Rinalds  and
      Marrese-Taylor, Edison",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italy",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.111",
    pages = "1233--1238"
}