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.
Original language | English |
---|---|
Title of host publication | ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 349-356 |
Number of pages | 8 |
ISBN (Print) | 9781479958771 |
DOIs | |
Publication status | Published - 10 Oct 2014 |
Event | 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 - Beijing, China Duration: 17 Aug 2014 → 20 Aug 2014 |
Conference
Conference | 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 |
---|---|
Country/Territory | China |
City | Beijing |
Period | 17/08/14 → 20/08/14 |