Exploring Optimism and Pessimism in Online Discourse of Individuals with Depression
Abstract: The relationship between depression and the concepts of optimism and pessimism has been extensively researched by psychologists. In this paper, we use computational approaches to study how optimism and pessimism are expressed in the online discourse of people diagnosed with depression. Publicly available datasets are used for the development of an optimism/pessimism detection model, as well as for the analyses performed on social media posts of individuals with depression, as measured by BDI-II, a validated questionnaire for assessing depression. To analyze the optimistic and pessimistic posts by individuals with depression, we use LIWC features and perform topic modeling. Our results show that while there might not be significant differences between the amount of optimistic versus pessimistic posts depressed and control individuals have, the content of the posts differ meaningfully, both in terms of linguistic features and approached topics.
Paper Type: Long
Research Area: Computational Social Science and Cultural Analytics
Research Area Keywords: quantitative analyses of news and/or social media
Contribution Types: Data analysis
Languages Studied: English
Submission Number: 8370
Loading