Polarization Is a key phenomenon which has been linked to Increasing disliking between people of opposite political groups. Furthermore, polarization can extend to new topics such as the debate on COVID-19 vaccines, making It more complex to coordinate efforts for such a problem. The social Identity approach (SIA) offers a robust theoretical framework for understanding Id entity-based social processes. This approach suggests that people's perceptions and behaviour depend on their group Identity (e.g.. Democrat vs Republican). In this article, we developed an opinion-dynamics model Integrating SIA to explore how polarization can extend to new topics. Furthermore, we developed this model from experiments with human participants. This allows us to use already validated micro-dynamic rules In the model. Empirical results show lack of repulsive effects, more attraction during ln-group Interactions and a new effect: Increased stubbornness when people a re exposed to opln Ions of an out-group member. The model was bu lit ml m Ickl ng the Interaction structure of the experiIment. At each Iteration, an agent observes the opinion of another agent. Depending on their respective groups the agent will experience a stronger or weaker attractive force, together with some noise. This model was able to produce polarization without the use of repulsive forces. Furthermore, the sensitivity analysis tells us that polarization In new topics can appear when all the following conditions are satisfied: (1) each person recognizes who Is belonging to which political group, (2) there are more ln-group than out-group Interactions and (3) there Is some Initial asymmetry on the topic.