ALGORITHMIC NEWS EXPOSURE AND MISINFORMATION SUSCEPTIBILITY: A STUDY OF SOCIAL MEDIA USERS IN PAKISTAN

Abstract

The increasing reliance on social media as a primary news source has intensified concerns regarding the role of algorithmic systems in shaping information exposure and amplifying misinformation. This study examined the relationship between algorithmic news exposure and misinformation susceptibility among social media users in Pakistan. A quantitative, cross-sectional survey design was employed, and data were collected from 384 respondents selected through a convenience sampling technique. The study utilized validated scales to measure algorithmic news exposure, misinformation susceptibility, and digital literacy. Statistical analyses, including correlation and regression techniques, were applied using SPSS. The findings revealed a significant positive relationship between algorithmic news exposure and misinformation susceptibility, indicating that increased exposure to algorithmically curated content is associated with a higher likelihood of believing and engaging with misleading information. Conversely, digital literacy demonstrated a significant negative relationship with misinformation susceptibility, highlighting its protective role in reducing vulnerability to false information. The regression model explained a substantial proportion of variance in misinformation susceptibility, confirming the strong predictive influence of algorithmic exposure. The study concludes that algorithmic news systems are not neutral information channels but active contributors to misinformation dissemination in digital environments. It further emphasizes the need for enhanced digital literacy and regulatory oversight to mitigate the adverse effects of algorithm-driven content curation. The findings contribute to theoretical advancements in selective exposure and media effects literature while offering practical implications for policymakers, educators, and social media platforms