Abstract
Social capital is linked to mental illness. It has been proposed that higher social capital is associated with better mental well-being in both individuals and groups in offline setting. However, in online settings, the association between online social capital and mental health conditions has not yet been explored. Social media offer us a rich opportunity to determine the link between social capital and aspects of mental wellbeing. In this paper, we examine social capital based on levels of social connectivity of bloggers can be connected to aspects of depression in individuals and online depression community. We explore apparent properties of textual contents, including expressed emotions, language styles and latent topics, of a large corpus of blog posts, to analyze the aspect of social capital in the community. Using data collected from online Livejoumal depression community, we apply both statistical tests and machine learning approaches to examine how predictive factors vary between low and high social capital groups. Significant differences are found between low and high social capital groups when characterized by a set of latent topics, language features derived from blog posts, suggesting discriminative features, proved to be useful in the classification task. This shows that linguistic styles are better predictors than latent topics as features. The findings indicate the potential of using social media as a sensor for monitoring mental well-being in online settings.
Original language | English |
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Title of host publication | 2016 IEEE RIVF - International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for the Future (RIVF) |
Subtitle of host publication | November 07-09, 2016 Thuyloi University, Hanoi, Vietnam - Main Proceedings |
Editors | Tru Cao, Yo-Sung Ho |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 61-66 |
Number of pages | 6 |
ISBN (Electronic) | 9781509041329 |
ISBN (Print) | 9781509041336 |
DOIs | |
Publication status | Published - 27 Dec 2016 |
Externally published | Yes |
Event | IEEE RIVF International Conference on Computing and Communication Technologies 2016 - Hanoi, Vietnam Duration: 7 Nov 2016 → 9 Nov 2016 Conference number: 12th http://rivf2016.tlu.edu.vn/ |
Conference
Conference | IEEE RIVF International Conference on Computing and Communication Technologies 2016 |
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Abbreviated title | RIVF 2016 |
Country/Territory | Vietnam |
City | Hanoi |
Period | 7/11/16 → 9/11/16 |
Internet address |
Keywords
- affective information
- latent topics
- mental health
- online social capital
- psycholinguistics
- social media