Using Twitter to learn about the autism community

Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines pertaining to the treatment and management of the disorder is crucial. Yet evidence suggests that policy makers and medical practitioners do not always have a good understanding of the practices and relevant beliefs of ASD-afflicted individuals' carers who often follow questionable recommendations and adopt advice poorly supported by scientific data. The key goal of the present work is to explore the idea that Twitter, as a highly popular platform for information exchange, could be used as a data-mining source to learn about the population affected by ASD -- their behaviour, concerns, needs etc. To this end, using a large data set of over 11 million harvested tweets as the basis for our investigation, we describe 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.Comment: Social Network Analysis and Mining, 201

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Spartan Daily, April 16, 2019

Volume 152, Issue 32https://scholarworks.sjsu.edu/spartan_daily_2019/1031/thumbnail.jp

The Daily Texan

Texas Student Medi

The Daily Texan

Texas Student Medi

The New Hampshire, Vol. 105, No. 41 (Apr. 7, 2016)

An independent student produced newspaper from the University of New Hampshire

Reaching out with OER: the new role of public-facing open scholar

Open educational resources (OER) and, more recently, open educational practices (OEP) have been widely promoted as a means of increasing openness in higher education (HE). Thus far, such openness has been limited by OER provision typically being supplier-driven and contained within the boundaries of HE. Seeking to explore ways in which OEP might become more needs-led we conceptualised a new ‘public-facing open scholar’ role involving academics working with online communities to source and develop OER to meet their needs. To explore the scope for this role we focused on the voluntary sector, which we felt might particularly benefit from such collaboration. We evaluated four representative communities for evidence of their being self-educating (thereby offering the potential for academics to contribute) and for any existing learning dimension. We found that all four communities were self-educating and each included learning infrastructure elements, for example provision for web chats with ‘experts’, together with evidence of receptiveness to academic collaboration. This indicated that there was scope for the role of public-facing open scholar. We therefore developed detailed guidelines for performing the role, which has the potential to be applied beyond the voluntary sector and to greatly extend the beneficial impact of existing OER, prompting institutions to release new OER in response to the needs of people outside HE

The Price Of “Normal”: Masking In The Autistic Community

The Autistic community has a rich history that often includes poor mental health outcomes due to the increased stress and anxiety surrounding the push to have “normal” social skills. On Twitter, many autistic people utilize a hashtag to connect with others in the online Autistic community. This qualitative study analyzes the Twitter hashtag, #ActuallyAutistic, to understand masking and camouflaging from the autistic point of view. A qualitative descriptive approach was used to perform this analysis. The themes found emphasize the need for professionals to increase their understanding of the Autistic community’s value and contributions. By improving the ability of non-autistic professionals to listen directly to the Autistic community’s wants, needs, and desires, strengths of the group are reinforced. The purpose of this research is to increase awareness and understanding of autistic voices. Discussion includes implications for occupational therapists in the use of strengths-based approaches to improve client outcomes in the Autistic community