Talking past each other in the cultural war area: Testing the efficacy of the moral attitude dynamic model to achieve accurate disagreement

This study evaluates the Moral Attitude Dynamic Model (MADM) as a tool to defuse conflicts tensions in two contemporary cases. It conducts a moral diagnosis on genetically modified (GM) food and abortion related tweets. Supporters’ and opponents’ tweets were identified using supervised machine learning classifiers for each issue separately. Distributed Dictionary Representation (DDR), a Natural Language Processing tool was adopted to quantify supporters’ and opponents’ moral stances along the enhanced contingency continuum (the key construct of MADM). The results reveal that serval types of misconceptions have been overlooked by both opponents and supporters of each issue. Multilevel linear modeling was then employed to investigate the quantified moral stances and to develop coping strategies for each group. Moreover, this study adopts computational methods for implementing MADM, enabling real-time tracking and analysis of target publics’ attitudes towards specific issues for more proactive and effective conflict management in polarized contexts. This is the first study to apply MADM in the context of polarization management. It expands the application of both Contingency Theory and Moral Foundation Theory (MFT) to polarization management as MADM bridges Contingency Theory and MFT. Furthermore, this study advances MFT methodologically by being the first to examine the moral loadings across all six innate moral foundations using computational methods. • Applied computational methods to enable real-time public opinion and moral-stance analysis. • Identified overlooked moral concerns that contribute to polarization on contentious issues. • Developed strategies to defuse culture-war tensions by improving cross-group understanding. • Presented the first application of the Moral Attitude Dynamic Model to political polarization. • Expanded the practical scope of Contingency Theory and Moral Foundation Theory for polarization management.