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Social Network Analysis and Mining

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01-12-2015 | Original Article

Using Twitter to learn about the autism community

Authors: Adham Beykikhoshk, Ognjen Arandjelović, Dinh Phung, Svetha Venkatesh, Terry Caelli

Published in: Social Network Analysis and Mining | Issue 1/2015

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Abstract

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.

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Title: Using Twitter to learn about the autism community
Authors: Adham Beykikhoshk
Ognjen Arandjelović
Dinh Phung
Svetha Venkatesh
Terry Caelli
Publication date: 01-12-2015
Publisher: Springer Vienna
Published in: Social Network Analysis and Mining / Issue 1/2015
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-015-0261-5

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