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Using linguistic and topic analysis to classify sub-groups of online depression communities

Nguyen, T, O Dea, B, Larsen, M, Phung, D, Venkatesh, S and Christensen, H 2017, Using linguistic and topic analysis to classify sub-groups of online depression communities, Multimedia tools and applications, vol. 76, no. 8, pp. 10653-10676, doi: 10.1007/s11042-015-3128-x.

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Title Using linguistic and topic analysis to classify sub-groups of online depression communities
Author(s) Nguyen, TORCID iD for Nguyen, T orcid.org/0000-0003-3467-8963
O Dea, B
Larsen, M
Phung, DORCID iD for Phung, D orcid.org/0000-0002-9977-8247
Venkatesh, SORCID iD for Venkatesh, S orcid.org/0000-0001-8675-6631
Christensen, H
Journal name Multimedia tools and applications
Volume number 76
Issue number 8
Start page 10653
End page 10676
Total pages 24
Publisher Springer
Place of publication Amsterdam, The Netherlands
Publication date 2017-04
ISSN 1380-7501
1573-7721
Keyword(s) Social media
Mental health
Depression
Web community
Web-logs
Feature extraction
Textual cues
Language styles
Topics
Science & Technology
Technology
Computer Science, Information Systems
Computer Science, Software Engineering
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Engineering
HEALTH-CARE
SOCIAL NETWORKING
COLLEGE-STUDENTS
MENTAL-DISORDERS
HETEROGENEITY
EMOTION
TWITTER
MEDIA
BLOGS
Language eng
DOI 10.1007/s11042-015-3128-x
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 0 Not Applicable
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Springer Science+Business Media New York
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089947

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