@inbook{62c16275238947ffb6d8ff7711200cc2,
title = "Women worry about family, men about the economy: Gender differences in emotional responses to COVID-19",
abstract = "Among the critical challenges around the COVID-19 pandemic is dealing with the potentially detrimental effects on people{\textquoteright}s mental health. Designing appropriate interventions and identifying the concerns of those most at risk requires methods that can extract worries, concerns and emotional responses from text data. We examine gender differences and the effect of document length on worries about the ongoing COVID-19 situation. Our findings suggest that i) short texts do not offer as adequate insights into psychological processes as longer texts. We further find ii) marked gender differences in topics concerning emotional responses. Women worried more about their loved ones and severe health concerns while men were more occupied with effects on the economy and society. This paper adds to the understanding of general gender differences in language found elsewhere, and shows that the current unique circumstances likely amplified these effects. We close this paper with a call for more high-quality datasets due to the limitations of Tweet-sized data.",
keywords = "COVID-19, Emotions, Gender differences, Language",
author = "{van der Vegt}, Isabelle and Bennett Kleinberg",
note = "Series Title: Lecture Notes in Computer Science",
year = "2020",
doi = "10.1007/978-3-030-60975-7_29",
language = "English",
isbn = "9783030609740",
volume = "12467",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "397--409",
editor = "Samin Aref and Kalina Bontcheva and Marco Braghieri and Frank Dignum and Fosca Giannotti and Francesco Grisolia and Dino Pedreschi",
booktitle = "Social Informatics",
}