Visualization analysis for emotional characteristics of autism spectrum disorder from cinemetrics perspective

TL;DR

This paper uses film analysis to study emotional characteristics of autism spectrum disorder, offering new insights through quantitative methods.

Contribution

The study introduces cinemetrics as a novel approach to quantitatively analyze emotional characteristics of ASD in films.

Findings

ASL values are consistently higher than MSL values, indicating a systematic rhythmic pattern in film editing.

Emotional characteristics of autistic individuals in films differ significantly in shot length, editing rate, camera movement, and composition.

Quantitative analysis provides objective data for ASD emotional studies and potential applications in training and intervention.

Abstract

The attention paid to Autism Spectrum Disorder (ASD) in film art and audiovisual communication has promoted the popularization of ASD knowledge and the development of treatment and education measures. As society pays more attention to ASD research and education, the limitations of traditional qualitative research methods are gradually becoming apparent, particularly in the dynamic and nuanced quantification of emotional characteristics, which hinders the practical application of research results. As an emerging research paradigm, cinemetrics provides new perspectives for film research. In this paper, 20 Chinese autism-themed films with 2,627 shots are selected and statistically analyzed in terms of style, rhythm, and space for their emotional character clips. Average Shot Length (ASL) and Median Shot Length (MSL) are compared using a Paired Samples t-test (t = 5.620, p < 0.001) to verify the statistical significance of rhythmic differences. The results indicate that the emotional characteristics of autistic individuals in various films differ significantly in terms of shot length, editing rate, camera movement, and composition. It is found that ASL values are consistently higher than MSL values indicates a systematic rhythmic pattern rather than random fluctuation, providing a reliable quantitative basis for further analysis. These quantitative analyses provide objective data support for the study of the emotional characteristics of ASD, and also offer potential references for practical applications such as expression recognition training and movement regulation programs. This paper can help the public to understand the emotional state of ASD people and open up new paths for future investigation of ASD intervention.

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