What Can We Learn From Almost a Decade of Food Tweets
Uga Sproģis, Matīss Rikters
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 contents of the corpus and demonstrate use-cases for the sub-corpora by training domain-specific question-answering and sentiment-analysis models using data from the corpus.
Results
| Task | Dataset | Metric | Value | Model |
|---|---|---|---|---|
| Sentiment Analysis | Latvian Twitter Eater Sentiment Dataset | Accuracy | 61.23 | Naive Bayes |
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