Using Twitter to learn about the autism community

Beykikhoshk, Adham, Arandjelović, Ognjen, Phung, Dinh, Venkatesh, Svetha and Caelli, Terry 2015, Using Twitter to learn about the autism community, Social network analysis and mining, vol. 5, no. 1, pp. 1-17, doi: 10.1007/s13278-015-0261-5.

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Title Using Twitter to learn about the autism community
Author(s) Beykikhoshk, Adham
Arandjelović, Ognjen
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Caelli, Terry
Journal name Social network analysis and mining
Volume number 5
Issue number 1
Start page 1
End page 17
Total pages 17
Publisher Springer
Place of publication New York, N.Y.
Publication date 2015-12
ISSN 1869-5450
1869-5469
Keyword(s) Social media
Big data
Asperger’s
Mental health
Health care
Public health
ASD
Summary Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision-making and communication of the latest guidelines pertaining to the treatment and management of the disorder is crucial. Yet evidence suggests that policy makers and medical practitioners do not always have a good understanding of the practices and relevant beliefs of ASD-afflicted individuals’ carers who often follow questionable recommendations and adopt advice poorly supported by scientific data. The key goal of the present work is to explore the idea that Twitter, as a highly popular platform for information exchange, could be used as a data-mining source to learn about the population affected by ASD—their behaviour, concerns, needs, etc. To this end, using a large data set of over 11 million harvested tweets as the basis for our investigation, we describe a series of experiments which examine a range of linguistic and semantic aspects of messages posted by individuals interested in ASD. Our findings, the first of their nature in the published scientific literature, strongly motivate additional research on this topic and present a methodological basis for further work.
Language eng
DOI 10.1007/s13278-015-0261-5
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
Copyright notice ©2015, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30076871

Document type: Journal Article
Collection: School of Information Technology
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