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. Attached Files Name Description MIMEType Size Downloads nguyen-autismblogs-post-2015.pdf Accepted version application/pdf 841.81KB 174 Title Autism blogs: expressed emotion, language styles and concerns in personal and community settings Author(s) Nguyen, Thin orcid.org/0000-0003-3467-8963 Duong, Thi Venkatesh, Svetha orcid.org/0000-0001-8675-6631 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 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Open Access Collection 2018 ERA Submission Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Tue, 25 Aug 2015, 14:57:51 EST Wed, 26 Aug 2015, 05:07:24 EST Wed, 26 Aug 2015, 08:16:11 EST Wed, 26 Aug 2015, 08:22:20 EST Fri, 09 Oct 2015, 17:09:20 EST Mon, 12 Oct 2015, 16:13:56 EST Wed, 14 Oct 2015, 14:32:10 EST Fri, 12 Feb 2016, 14:59:40 EST Sat, 13 Feb 2016, 05:08:22 EST Mon, 11 Apr 2016, 11:23:56 EST Mon, 11 Apr 2016, 11:26:32 EST Fri, 05 Oct 2018, 11:29:22 EST Fri, 19 Oct 2018, 12:48:27 EST Filtered Full Citation counts:   Cited 8 times in TR Web of Science Cited 11 times in Scopus Search Google Scholar Access Statistics: 556 Abstract Views, 178 File Downloads  -  Detailed Statistics Created: Fri, 12 Feb 2016, 14:59:40 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.