arXiv
Open Access
2024
Annotations for Exploring Food Tweets From Multiple Aspects
Matīss Rikters
Edison Marrese-Taylor
Rinalds Vīksna
Abstrak
This research builds upon the Latvian Twitter Eater Corpus (LTEC), which is focused on the narrow domain of tweets related to food, drinks, eating and drinking. LTEC has been collected for more than 12 years and reaching almost 3 million tweets with the basic information as well as extended automatically and manually annotated metadata. In this paper we supplement the LTEC with manually annotated subsets of evaluation data for machine translation, named entity recognition, timeline-balanced sentiment analysis, and text-image relation classification. We experiment with each of the data sets using baseline models and highlight future challenges for various modelling approaches.
Penulis (3)
M
Matīss Rikters
E
Edison Marrese-Taylor
R
Rinalds Vīksna
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2024
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓