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What Can We Learn from Almost a Decade of Food Tweets
Uga Sproģis, Matīss Rikters
191 - 198
10.3233/FAIA200622
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 328: Human Language Technologies – The Baltic Perspective
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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