From Persuasion to Co-Creation: Hybrid Models for Social Identity-Driven Deliberation

G. Wright (2022) argues that persuasion often fails when social identity is threatened, advocating for co-creation approaches instead. Yet, in practice, deliberative processes can oscillate between these modes. This project would build a hybrid argumentation mining system that, using cues from text and participant profiles (e.g., via advanced NLP and ML methods from Singh et al., 2025), detects when social identity is invoked or threatened during argumentation. The system would then recommend or simulate a switch from a persuasion-based approach (classic argumentation mining) to a co-creative/integrative mode (e.g., seeking consensus or shared values). This adaptive modeling of deliberative strategies is novel and could significantly improve AI-mediated negotiations, online deliberation platforms, and our theoretical understanding of identity-driven argument dynamics.

References:

1. Persuasion or Co-creation? Social Identity Threat and the Mechanisms of Deliberative Transformation. G. Wright (2022). Special Issue: Psychological Phenomena in Democratic Deliberation.
2. A Review Article for Argumentation Mining of Text through Machine Learning Techniques and Strategies. Rudrendra Bahadur Singh, Shobhit Sinha, Ankita Singh (2025). Journal of Information Systems Engineering & Management.