This study assumes that judicial decisions, embodying legal justice and are not always matched to what the society actually believes as social justice. To find out how distant legal justice is from social justice, a video sharing social media channel...
This study assumes that judicial decisions, embodying legal justice and are not always matched to what the society actually believes as social justice. To find out how distant legal justice is from social justice, a video sharing social media channel managed by a traffic accident lawyer is selected as the research environment. Since the videos on the channel include judicial rulings and viewers' comments follow, the media platform provide suitable data for our study.
Given that the judicial ruling in the video is a proxy for legal justice and the collection of comments for social justice, we classified the comments into positive, negative, and neutral emotions using a machine learning ChatGPT. The comments labeled as positive emotions were interpreted as agreement with the ruling, and the comments labeled as negative were captured as disagreement. In addition, considering the features of vehicle accident judgments, we classified emotions in more details according to vehicle accident fault ratios and judgment levels. By doing so, this study provides theoretical and practical implications.
Our findings suggest that differences between social and legal justice may exist. Additionally, the degree of difference depends on factors such as accident negligence rates or judgmental outcomes.