What can we learn from almost a decade of food tweets

Uga Sproagis; Matīss Rikters

doi:10.3233/FAIA200622

What can we learn from almost a decade of food tweets

Uga Sproagis^*
, Matīss Rikters

^*Corresponding author for this work

University of Latvia
The University of Tokyo
Datorikas fakultāte Maģistrantūra

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

5 Citations (Scopus)

Abstract

We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of over 8 years and includes over 2 million tweets entailed with additional useful data. We also separate two sub-corpora of question and answer tweets and sentiment annotated tweets. We analyse the contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using the data from the corpus.

Original language	English
Title of host publication	Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020
Editors	Andrius Utka, Jurgita Vaicenoniene, Jolanta Kovalevskaite, Danguole Kalinauskaite
Place of Publication	Amsterdam
Publisher	IOS Press
Pages	191-198
ISBN (Print)	9781643681160
DOIs	https://doi.org/10.3233/FAIA200622
Publication status	Published - 15 Sept 2020

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	328
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

OECD Field of Science

1.2 Computer and Information Sciences

Keywords

Annotated corpora
Food data
Latvian
Social networks

Access to Document

10.3233/FAIA200622

Cite this

Sproagis, U., & Rikters, M. (2020). What can we learn from almost a decade of food tweets. In A. Utka, J. Vaicenoniene, J. Kovalevskaite, & D. Kalinauskaite (Eds.), Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020 (pp. 191-198). (Frontiers in Artificial Intelligence and Applications; Vol. 328). IOS Press. https://doi.org/10.3233/FAIA200622

Sproagis, Uga ; Rikters, Matīss. / What can we learn from almost a decade of food tweets. Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020. editor / Andrius Utka ; Jurgita Vaicenoniene ; Jolanta Kovalevskaite ; Danguole Kalinauskaite. Amsterdam : IOS Press, 2020. pp. 191-198 (Frontiers in Artificial Intelligence and Applications).

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abstract = "We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of over 8 years and includes over 2 million tweets entailed with additional useful data. We also separate two sub-corpora of question and answer tweets and sentiment annotated tweets. We analyse the contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using the data from the corpus.",

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author = "Uga Sproagis and Matīss Rikters",

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Sproagis, U & Rikters, M 2020, What can we learn from almost a decade of food tweets. in A Utka, J Vaicenoniene, J Kovalevskaite & D Kalinauskaite (eds), Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020. Frontiers in Artificial Intelligence and Applications, vol. 328, IOS Press, Amsterdam, pp. 191-198. https://doi.org/10.3233/FAIA200622

What can we learn from almost a decade of food tweets. / Sproagis, Uga; Rikters, Matīss.
Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020. ed. / Andrius Utka; Jurgita Vaicenoniene; Jolanta Kovalevskaite; Danguole Kalinauskaite. Amsterdam: IOS Press, 2020. p. 191-198 (Frontiers in Artificial Intelligence and Applications; Vol. 328).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

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AU - Rikters, Matīss

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N2 - We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of over 8 years and includes over 2 million tweets entailed with additional useful data. We also separate two sub-corpora of question and answer tweets and sentiment annotated tweets. We analyse the contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using the data from the corpus.

AB - We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of over 8 years and includes over 2 million tweets entailed with additional useful data. We also separate two sub-corpora of question and answer tweets and sentiment annotated tweets. We analyse the contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using the data from the corpus.

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KW - Food data

KW - Latvian

KW - Social networks

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A2 - Kalinauskaite, Danguole

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Sproagis U, Rikters M. What can we learn from almost a decade of food tweets. In Utka A, Vaicenoniene J, Kovalevskaite J, Kalinauskaite D, editors, Human Language Technologies - The Baltic Perspective - Proceedings of the 9th International Conference Baltic HLT 2020. Amsterdam: IOS Press. 2020. p. 191-198. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/FAIA200622

What can we learn from almost a decade of food tweets

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