# What Can We Learn From Almost a Decade of Food Tweets

Source: [What Can We Learn From Almost a Decade of Food Tweets](<https://www.sota2.com/research/paper/68fa684b1e209131cea1b2dc>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-01T13:06:29.989Z

Authors: Uga Spro\\c{g}is, Mat\\=iss Rikters

Published: 2020-07-10T06:36:13.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2007.05194>)

[PDF](<https://arxiv.org/pdf/2007.05194.pdf>)

[Implementation](<https://github.com/Usprogis/Latvian-Twitter-Eater-Corpus>)