TY - JOUR
T1 - Using Twitter to learn about the autism community
AU - Beykikhoshk, Adham
AU - Arandjelović, Ognjen
AU - Phung, Dinh
AU - Venkatesh, Svetha
AU - Caelli, Terry
PY - 2015/12
Y1 - 2015/12
N2 - 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.
AB - 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.
KW - ASD
KW - Asperger’s
KW - Big data
KW - Health care
KW - Mental health
KW - Public health
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=84947275672&partnerID=8YFLogxK
U2 - 10.1007/s13278-015-0261-5
DO - 10.1007/s13278-015-0261-5
M3 - Article
AN - SCOPUS:84947275672
SN - 1869-5450
VL - 5
JO - Social Network Analysis and Mining
JF - Social Network Analysis and Mining
IS - 1
M1 - 22
ER -