PROJECT TITLE :

Autism Blogs: Expressed Emotion, Language Styles and Concerns in Personal and Community Settings

ABSTRACT:

The Internet has provided an ever increasingly popular platform for individuals to voice their thoughts, and like-minded people to share stories. This unintentionally leaves characteristics of individuals and communities, which are typically tough to be collected in ancient studies. People with autism are such a case, in which the Internet could facilitate even additional communication given its social-spatial distance being a characteristic preference for individuals with autism. Previous studies examined the traces left within the posts of online autism communities (Autism) compared with alternative online communities (Management). This work further investigates these online populations through the contents of not only their posts however additionally their comments. We have a tendency to first compare the Autism and Control blogs based mostly on three options: topics, language styles and affective data. The autism groups are then any examined, based on the same 3 features, by wanting at their personal (Personal) and community (Community) blogs separately. Machine learning and statistical ways are used to discriminate blog contents in both cases. All three options are found to be significantly completely different between Autism and Management, and between autism Personal and Community. These features conjointly show smart indicative power in prediction of autism blogs in both personal and community settings.