DocumentCode :
116473
Title :
Data-mining twitter and the autism spectrum disorder: A Pilot study
Author :
Beykikhoshk, Adham ; Arandjelovic, Ognjen ; Dinh Phung ; Venkatesh, Svetha ; Caelli, Terry
Author_Institution :
Centre for Pattern Recognition & Data Analytics, Deakin Univ., Geelong, VIC, Australia
fYear :
2014
fDate :
17-20 Aug. 2014
Firstpage :
349
Lastpage :
356
Abstract :
The autism spectrum disorder (ASD) is increasingly being recognized as a major public health issue which affects approximately 0.5-0.6% of the population. Promoting the general awareness of the disorder, increasing the engagement with the affected individuals and their carers, and understanding the success of penetration of the current clinical recommendations in the target communities, is crucial in driving research as well as policy. The aim of the present work is to investigate if Twitter, as a highly popular platform for information exchange, can be used as a data-mining source which could aid in the aforementioned challenges. Specifically, using a large data set of harvested tweets, we present 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.
Keywords :
data mining; medical computing; social networking (online); ASD; autism spectrum disorder; clinical recommendations; data-mining Twitter; information exchange; linguistic aspects; public health; semantic aspects; Autism; Communities; Conferences; Data mining; Pragmatics; Twitter; Variable speed drives;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/ASONAM.2014.6921609
Filename :
6921609
Link To Document :
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