arXiv:2606.13187v1 Announce Type: new Abstract: Bioethical debates increasingly unfold on social media, yet stance detection research lacks large-scale, domain-specific resources for modeling such context-dependent discourse. We present BioStance, a context-aware dataset of 39,600 annotated Post-Comment pairs from Reddit bioethical discussions. BioStance covers six controversial targets across three dimensions of bioethical controversy: fundamental value conflicts, individual liberty versus collective responsibility, and technological uncertainty. Each instance preserves hierarchical conversat
The proliferation of complex bioethical discussions on social media necessitates more sophisticated AI tools for understanding and navigating public sentiment, reflecting a growing need for nuanced digital discourse analysis.
This new dataset addresses a critical gap in AI's ability to interpret human-like arguments and stances in sensitive, context-dependent domains, crucial for developing more robust and ethically aware AI systems.
This dataset improves the ability of AI models to perform stance detection in a highly nuanced and controversial domain, potentially enhancing automated content moderation, public opinion analysis, and AI-assisted ethical decision-making.
- · AI researchers
- · Social media platforms
- · Computational ethics
- · Public policy analysts
- · Platforms with unsophisticated content moderation
- · Researchers lacking domain-specific data
AI models will become more adept at identifying nuanced opinions and arguments in complex bioethical discussions.
Improved stance detection could lead to more effective and fair content moderation policies on social media, especially around sensitive topics.
The application of such AI to public discourse might shape how bioethical controversies are discussed and understood, influencing public opinion and policy outcomes.
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