EmoEvent: A multilingual emotion corpus based on different events

In recent years emotion detection in text has become more popular due to its potential applications in fields such as psychology, marketing, political science, and artificial intelligence, among others. While opinion mining is a well-established task with many standard datasets and well-defined methodologies, emotion mining has received less attention due to its complexity. In particular, the annotated gold standard resources available are not enough. In order to address this shortage, we present a multilingual emotion dataset based on different events that took place in April 2019. We collected tweets from the Twitter platform. Then one of seven emotions, six Ekman's basic emotions plus the “neutral or other emotions”, was labeled on each tweet by 3 Amazon MTurkers. A total of 8,409 in Spanish and 7,303 in English were labeled. In addition, each tweet was also labeled as offensive or non-offensive. We report some linguistic statistics about the dataset in order to observe the difference between English and Spanish speakers when they express emotions related to the same events. Moreover, in order to validate the effectiveness of the dataset, we also propose a machine learning approach for automatically detecting emotions in tweets for both languages, English and Spanish.