What Can We Learn From Almost a Decade of Food Tweets
2020-07-10Code Available0· sign in to hype
Uga Sproģis, Matīss Rikters
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/Usprogis/Latvian-Twitter-Eater-CorpusOfficialIn papernone★ 7
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.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| Latvian Twitter Eater Sentiment Dataset | Naive Bayes | Accuracy | 61.23 | — | Unverified |