ALGORITHMIC ECHO CHAMBERS, STIGMATIZATION, AND INTERGROUP HOSTILITY: UNDERSTANDING THE SOCIAL PSYCHOLOGY OF SECTARIAN DIVIDES IN PUNJAB THROUGH AI-DRIVEN MEDIA EXPOSURE

Abstract

The emergence of AI-based social media platforms has dramatically changed the way people consume content, and in most cases, the use of social media has contributed to the development of social media echo chambers that promote facing the beliefs and restrict exposure to other forms of thinking. These echo chambers can contribute to worse stigmatization of outgroups and more intergroup hostility in religious and sectarian societies such as Punjab, Pakistan. The current research examined how AI-driven exposure to the echo chamber, stigmatization of religious outgroups, and intergroup hostility among mixed urban-rural young people (18-30 years old, N = 320) are related, with empathy serving as a moderating factor. A cross-sectional research design was used, which is quantitative in nature and the data were gathered through standardized psychological scales. Findings revealed that exposure to algorithmically curated content positively anticipated stigmatization as well as intergroup hostility. These relationships were greatly mediated by empathy whereby higher empathy alleviated the negative impact of the exposure to the echo chambers. The results indicate the psychological processes by which AI-based media forms sectarian attitudes and propose that the promotion of empathy can offset the effect of polarized online spaces. These findings have an implication to both digital literacy programs and social media policy as well as intercessions that maybe used to encourage intergroup knowledge and social cohesion among Pakistan youth.