Twitter as a Topic Analysis Tool for Autism Spectrum Disorder: A Text Mining Approach

ID: 54577 Type: Full Paper
  1. Okan Arslan and Fethi Inan, Texas Tech University, United States

Thursday, March 21 10:45 AM-11:15 AM Location: Sunset 4 View on map

No presider for this session.

Abstract: The purpose of this study is to analyze social media trends for Autism Spectrum Disorder (ASD) by using twitter data to understand the common topics related to ASD in twitter. To do so, #autism hashtag was used to gather data from twitter and Latent Dirichlet Allocation (LDA) algorithm was used as a text mining approach for topic analysis. According to the LDA and content analysis results, the most frequent topics about autism mentioned by the twitter users are “need for parental support”, “communication and interactions skills and resources”, and “cause of autism”.

Topics

Conference attendees are able to comment on papers, view the full text and slides, and attend live presentations. If you are an attendee, please login to get full access.