Measuring political polarization through visible interactions between religious and non-religious citizens.

This study offers a new method for measuring polarization by using advanced computer vision techniques that involve object detection and measurements of physical distances between pedestrians. Motivated by escalating political polarization around the world, and specifically by the ideological divide between secularism and political Islam in Turkey, we analyze more than 1,400 publicly available YouTube videos recorded on the streets of Turkey. From these videos, we extract and use approximately 170,000 frames that show pedestrians. The analysis detects and categorizes pedestrians based on their gender and level of religiosity by using the YOLOv5 algorithm and develops and refines two innovative distance estimation techniques for calculating the relative distances between pairs of pedestrians. Our unique technical approach allows us to convert the 2D distances in the street videos into 3D relative distances between pedestrians of different genders and levels of religiosity. These distances are then used as a proxy for measuring the extent of polarization. The study concludes that social factors significantly influence these distances, with individuals from similar backgrounds (i.e., religious people, religious females, and non-religious females) tending to walk closer to their in-group. The greatest distances are measured between non-religious males and religious females, as well as between religious females and non-religious males, reflecting traditional gender boundaries in predominantly Muslim communities and highlighting how religious and cultural norms shape social interactions. The image dataset we have assembled stands as the most extensive collection of thematic street imagery found in computational social science research and represents the largest dataset ever gathered for analyzing political polarization in Turkey.