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Autism blogs: expressed emotion, language styles and concerns in personal and community settings

Nguyen, Thin, Duong, Thi, Venkatesh, Svetha and Phung, Dinh 2015, Autism blogs: expressed emotion, language styles and concerns in personal and community settings, IEEE transactions on affective computing, vol. 6, no. 3, July-September, pp. 312-323, doi: 10.1109/TAFFC.2015.2400912.

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Title Autism blogs: expressed emotion, language styles and concerns in personal and community settings
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Duong, Thi
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Journal name IEEE transactions on affective computing
Volume number 6
Issue number 3
Season July-September
Start page 312
End page 323
Total pages 12
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2015-07
ISSN 1949-3045
Keyword(s) affective norms
language styles
topics
psychological health
autism
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Cybernetics
Computer Science
SPECTRUM DISORDERS
COLLEGE-STUDENTS
DEPRESSION
TEXT
Summary The Internet has provided an ever increasingly popular platform for individuals to voice their thoughts, and like-minded people to share stories. This unintentionally leaves characteristics of individuals and communities, which are often difficult to be collected in traditional studies. Individuals with autism are such a case, in which the Internet could facilitate even more communication given its social-spatial distance being a characteristic preference for individuals with autism. Previous studies examined the traces left in the posts of online autism communities (Autism) in comparison with other online communities (Control). This work further investigates these online populations through the contents of not only their posts but also their comments. We first compare the Autism and Control blogs based on three features: topics, language styles and affective information. The autism groups are then further examined, based on the same three features, by looking at their personal (Personal) and community (Community) blogs separately. Machine learning and statistical methods are used to discriminate blog contents in both cases. All three features are found to be significantly different between Autism and Control, and between autism Personal and Community. These features also show good indicative power in prediction of autism blogs in both personal and community settings.
Language eng
DOI 10.1109/TAFFC.2015.2400912
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
ERA Research output type C Journal article
Grant ID ARC LP140100240
Copyright notice ©2015, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30076685

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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.