You are not logged in.

Connectivity, online social capital, and mood : a Bayesian nonparametric analysis

Phung, Dinh, Gupta, Sunil Kumar, Nguyen, Thin and Venkatesh, Svetha 2013, Connectivity, online social capital, and mood : a Bayesian nonparametric analysis, IEEE transactions on multimedia, vol. 15, no. 6, pp. 1316-1325, doi: 10.1109/TMM.2013.2264274.

Attached Files
Name Description MIMEType Size Downloads

Title Connectivity, online social capital, and mood : a Bayesian nonparametric analysis
Author(s) Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Gupta, Sunil KumarORCID iD for Gupta, Sunil Kumar orcid.org/0000-0002-3308-1930
Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Journal name IEEE transactions on multimedia
Volume number 15
Issue number 6
Start page 1316
End page 1325
Total pages 10
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2013
ISSN 1520-9210
1941-0077
Summary Social capital indicative of community interaction and support is intrinsically linked to mental health. Increasing online presence is now the norm. Whilst social capital and its impact on social networks has been examined, its underlying connection to emotional response such as mood, has not been investigated. This paper studies this phenomena, revisiting the concept of “online social capital†in social media communities using measurable aspects of social participation and social support. We establish the link between online capital derived from social media and mood, demonstrating results for different cohorts of social capital and social connectivity. We use novel Bayesian nonparametric factor analysis to extract the shared and individual factors in mood transition across groups of users of different levels of connectivity, quantifying patterns and degree of mood transitions. Using more than 1.6 million users from Live Journal, we show quantitatively that groups with lower social capital have fewer positive moods and more negative moods, than groups with higher social capital. We show similar effects in mood transitions. We establish a framework of how social media can be used as a barometer for mood. The significance lies in the importance of online social capital to mental well-being in overall. In establishing the link between mood and social capital in online communities, this work may suggest the foundation of new systems to monitor online mental well-being.
Language eng
DOI 10.1109/TMM.2013.2264274
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2013, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30057795

Document type: Journal Article
Collection: Centre for Pattern Recognition and Data Analytics
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 7 times in TR Web of Science
Scopus Citation Count Cited 10 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 308 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Tue, 12 Nov 2013, 14:58:52 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.