What Can We Learn From Almost a Decade of Food Tweets

TL;DR

This paper introduces a large, annotated Latvian food-related Twitter corpus collected over 8 years, and demonstrates its usefulness for training domain-specific question-answering and sentiment analysis models.

Contribution

The paper presents the Latvian Twitter Eater Corpus, a comprehensive, multi-annotated dataset for food-related tweets, and showcases its application in NLP tasks.

Findings

Successful training of domain-specific question-answering models

Effective sentiment analysis using the corpus data

Demonstration of corpus utility for NLP research

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.