2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) · 2014 · 41 citations · 21 references
ComputingComputer ScienceData ScienceAutism Spectrum DisordersData MiningNatural Language ProcessingClinical Natural Language ProcessingSocial MediaText MiningAwarenessSocial Media MiningTweet Sentiment Analysis
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.
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