Autonomous driving paper index
Counter-protesters against hate speech in Japan: negative framing by police, media, and activists
One-line summary
Abstract In 2013, counter-protests emerged in Japan in response to escalating far-right demonstrations featuring hate speech.
Engineering notes
Key topics: autonomous driving, control. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Abstract In 2013, counter-protests emerged in Japan in response to escalating far-right demonstrations featuring hate speech. Counter-protesters formed a movement described as “Liberal Antifa.” Many used Antifa symbols, yet the movement remained non-violent and distinct from the more militant Antifa in other Western countries. They verbally confronted far-right activists and used electronic noise, helping reduce far-right demonstrations. From the summer of 2025, their visibility once again increased through protests against the Sanseito. This paper examines how, despite these contributions, counter-protesters have been negatively framed across three layers: policing, news coverage, and activist discourse. Using forty-six qualitative interviews with forty protesters (2017–2023) and content analysis of activist publications and news reports, this study investigates the framing process and effects. It shows that these layers mutually reinforced negative portrayals, where policing with arrests on minor charges and media reliance on police press releases or sensationalism prioritised “law and order” over protest rights. Furthermore, activist discourse used historical analogies to delegitimise counter-protesters. This study elucidates the current dynamics of social control in Japan, including the blurring of boundaries between institutional media and online activist discourse, which leads to stigmatisation of counter-protesters.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments