Exploring Reliability of Gold Labels for Emotion Detection in Twitter

Autor:	Sanja Štajner
Rok vydání:	2021
Předmět:	ComputingMethodologies_PATTERNRECOGNITION business.industry Computer science Emotion detection Social media Artificial intelligence computer.software_genre business computer Natural language processing Reliability (statistics)
Zdroj:	RANLP
DOI:	10.26615/978-954-452-072-4_151
Popis:	Emotion detection from social media posts has attracted noticeable attention from natural language processing (NLP) community in recent years. The ways for obtaining gold labels for training and testing of the systems for automatic emotion detection differ significantly from one study to another, and pose the question of reliability of gold labels and obtained classification results. This study systematically explores several ways for obtaining gold labels for Ekman’s emotion model on Twitter data and the influence of the chosen strategy on the manual classification results.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6edf124d908a0a7c54515ab52703e5bb https://doi.org/10.26615/978-954-452-072-4_151 Zobrazit plný text záznamu