Discussions of Asperger Syndrome on Social Media: Content and Sentiment Analysis on Twitter

Digital trends in autism: a scoping review exploring coverage of autism across YouTube, Twitter, and Facebook

Autism continues to be a leading neurodevelopmental disorder across adult and pediatric populations that transcends racial, ethnic, age, and socioeconomic groups worldwide. Autism care and treatment also exerts immense costs on the healthcare system and lost productivity which are partly attributed to the existing resource limitations globally. Organizations, campaigns, and policies exist worldwide in increasing equity and accessibility of resources and services to individuals with autism. In the context of our digital era, a wealth of information is also more readily available on autism through electronic communication including social media platforms. As YouTube, Twitter and Facebook are ever-growing and among the leading social media platforms in contemporary times, examination of content covered on autism across these communication mediums is timely and warranted. This review consolidates findings from 32 sources on the sources, formats, and nature of content covered on YouTube, Twitter, and Facebook pertaining to a wealth of dimensions surrounding autism. Strengths and limitations of the studies and endeavors are presented. Implications for future campaign development, health equity, health policy, neurodiversity, and patient care are also delineated. Lastly, recommendations for future research and practice are discussed which present directions for tapping into the potential of YouTube, Twitter, and Facebook as health communication mediums across the ever-changing autism landscape.

Social media interventions for autistic individuals: Systematic review

Background

Research on the use of digital technologies for delivering behavioral interventions has shown mixed evidence on their efficacy for improving both autistic symptoms and co-occurring psychiatric disorders. Little knowledge exists on the specific use or efficacy of using social media in interventions aimed at autistic individuals.

Objective

To review and describe the current existing evidence-based research on the use of social media in interventions aimed at autistic individuals.

Methods

A search was conducted across 8 databases (PubMed; EMBASE; Cochrane Library; PsycInfo; ERIC; Education Source; Web of Science; and IEEE Xplore). We included primary studies and reviews that dealt with autism spectrum disorder (ASD); described interventions that use social media; and reported results from the intervention. The quality of the evidence of the included primary studies was graded according to the GRADE criteria, and the risk of bias in systematic reviews was assessed by drawing on the AMSTAR guidelines. Results were synthesized and sorted by quality of evidence.

Results

A total of nine articles were included in this review: eight primary studies (five non-randomized interventions and three randomized interventions) and one systematic review. The total number of participants with an ASD-diagnosis in the included studies was 164 (aged 5 to 22 years old). Studies weighted as being of moderate quality of evidence have reported significant positive effects in the groups that received the social media interventions: increased social engagement and participation in life situations; increased physical activity level; increased improvement on occupational performance, specified goals, and behavioral problems; and decreased plaque scores coupled with parent reports of intervention success. None of the studies have reported any negative effects linked to social media interventions.

Conclusion

There is very little evidence of good quality on the use of social media in interventions aimed at autistic individuals. While there is a need for more high-quality studies, all the included studies, with one exception found positive results of the interventions. These findings are encouraging, suggesting that social media-based interventions may in fact be useful for supporting behavioral changes in autistic individuals.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=337185, identifier CRD42022337185.

Asperger Syndrome (AS): A Review Article

A variant of autism spectrum disorder (ASD) known as Asperger syndrome (AS) is characterized by severe issues with interpersonal, verbal, and nonverbal communication as well as restricted and repetitive patterns of behavior and activities. Although there is no known cause for ASD, various genetic as well as non-genetic risk factors that may act either alone or in combination to induce ASD have been identified. The occurrence of ASD has been increasing worldwide. Co-occurring neuropsychological diseases are frequently present as well. The premise for diagnosis is the observation of abnormal conduct, with diagnostic criteria emphasizing limitations in social interaction and communication as well as constrained, repetitive behavioral patterns, activities, or hobbies. The degree of the illness and the presence of intellectual impairment have a significant impact on the prognosis. Like autism, Asperger's can neither be prevented nor treated. There is no specific medical therapy that can effectively cure all of the symptoms of autism. However, medications may be used as adjuvant therapy for maladaptive behaviors and co-occurring mental problems. The treatment aims to reduce core impairments, increase functional ability, and reduce harmful behaviors that could limit functional skills. It is crucial to provide proper care, establish supportive networks for individuals who are affected and their families, and use effective therapies to enhance functioning and results.

They May not Work! An Evaluation of Eleven Sentiment Analysis Tools on Seven Social Media Datasets

OBJECTIVE

Sentiment analysis is an important method for understanding emotions and opinions expressed through social media exchanges. Little work has been done to evaluate the performance of existing sentiment analysis tools on social media datasets, particularly those related to health, healthcare, or public health. This study aims to address the gap.

MATERIAL AND METHODS

We evaluated 11 commonly used sentiment analysis tools on five health-related social media datasets curated in previously published studies. These datasets include Human Papillomavirus Vaccine, Health Care Reform, COVID-19 Masking, Vitals.com Physician Reviews, and the Breast Cancer Forum from MedHelp.org. For comparison, we also analyzed two non-health datasets based on movie reviews and generic tweets. We conducted a qualitative error analysis on the social media posts that were incorrectly classified by all tools.

RESULTS

The existing sentiment analysis tools performed poorly with an average weighted F1 score below 0.6. The inter-tool agreement was also low; the average Fleiss Kappa score is 0.066. The qualitative error analysis identified two major causes for misclassification: (1) correct sentiment but on wrong subject(s) and (2) failure to properly interpret inexplicit/indirect sentiment expressions.

DISCUSSION

and Conclusion: The performance of the existing sentiment analysis tools is insufficient to generate accurate sentiment classification results. The low inter-tool agreement suggests that the conclusion of a study could be entirely driven by the idiosyncrasies of the tool selected, rather than by the data. This is very concerning especially if the results may be used to inform important policy decisions such as mask or vaccination mandates.