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Analysis of psycholinguistic processes and topics in online autism communities
conference contribution
posted on 2013-01-01, 00:00 authored by Thin NguyenThin Nguyen, Quoc-Dinh Phung, Svetha VenkateshSvetha VenkateshCurrent growth of individuals on the autism spectrum disorder (ASD) requires continuous support and care. With the popularity of social media, online communities of people affected by ASD emerge. This paper presents an analysis of these online communities through understanding aspects that differentiate such communities. In this paper, the aspects given are not expressed in terms of friendship, exchange of information, social support or recreation, but rather with regard to the topics and linguistic styles that people express in their on-line writing. Using data collected unobtrusively from LiveJournal, we analyze posts made by ten autism communities in conjunction with those made by a control group of standard communities. Significant differences have been found between autism and control communities when characterized by latent topics of discussion and psycholinguistic features. Latent topics are found to have greater predictive power than linguistic features when classifying blog posts as either autism or control community. This study suggests that data mining of online blogs has the potential to detect clinically meaningful data. It opens the door to possibilities including sentinel risk surveillance and harnessing the power in diverse large datasets.
History
Event
Multimedia and Expo. IEEE International Conference (14th : 2013 : San Jose, California)Pagination
1 - 6Publisher
IEEELocation
San Jose, CaliforniaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2013-07-15End date
2013-07-19ISBN-13
9781479900152Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2013, IEEETitle of proceedings
ICME 2013 : Proceedings of the 14th IEEE International Conference on Multimedia and ExpoUsage metrics
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