Among the critical challenges around the COVID-19 pandemic is dealing with the potentially detrimental effects on people’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.
|Title of host publication||Social Informatics|
|Subtitle of host publication||Proceedings 12th International Conference on Social Informatics, SocInfo|
|Editors||Samin Aref, Kalina Bontcheva, Marco Braghieri, Frank Dignum, Fosca Giannotti, Francesco Grisolia, Dino Pedreschi|
|Place of Publication||Cham|
|Publication status||Published - 2020|
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
- Gender differences