نظریه بازنمایی شناختی در رسانه‌های اجتماعی: تبیینی نوین از دوقطبی‌سازی سیاسی در ایران

Social media platforms have, in recent years, transformed into a key arena for shaping public opinion and reproducing socio-political cleavages in Iran. The current research, driven by the central question, "How does the interaction between social media, cognitive processes, and political narratives lead to socio-political polarization?", proposes a novel framework. Within this framework, the "Cognitive Representation Theory in Social Media" explains how media content reconstructs users' perceptions by activating cognitive biases, collective emotions, and attention-reinforcing algorithms. This, in turn, paves the way for the intensification of identity cleavages and political polarization. The theory’s conceptual model depicts a feedback loop illustrating the interaction among five key components: platform and algorithmic structures, individual cognitive processes, political-media narratives, collective behaviors, and foreign actors' interventions in the form of cognitive warfare. Utilizing secondary data analysis and theoretical analysis, this framework provides a deeper understanding of cognitive-media processes, enabling policy interventions in the domains of cognitive media literacy education, platform regulation, and cognitive defense. The findings indicate that platform algorithms systematically intensify polarization in Iran by reinforcing confirmation bias and fostering informational echo chambers and emotional narratives. The proposed theory also represents a step toward localizing the concepts of "perceptual warfare" and "cognitive representation" within the Iranian social context.
Introduction:
In recent years, social media in Iran has become one of the most significant platforms for shaping public opinion and reproducing socio-political divisions. Platforms such as Twitter, Instagram, and Telegram are not only tools for information dissemination and political interaction but, through engagement-enhancing architectures and personalization algorithms, they highlight emotional content aligned with users’ preexisting beliefs. This situation, combined with a lack of discursive diversity, cross-border interventions, and socio-economic factors, provides a fertile ground for the emergence and intensification of polarization.
This study addresses the central question: How does the interaction between social media, cognitive processes, and political narratives lead to socio-political polarization? It aims to present an interdisciplinary framework—Cognitive Representation Theory in Social Media —to explain this complex interaction.
Method:
This research employs a library-based study and theoretical analysis, integrating findings from cognitive science, communication studies, and political science. The literature on cognitive biases, platform algorithms, media framing, and political polarization was first reviewed. Subsequently, influential factors were identified at two levels:
- Micro level: perceptual processes, emotional responses, cognitive biases, and users’ media behaviors.
- Macro level: media policymaking, content personalization algorithms, discursive structures, and cognitive interventions.
These factors were synthesized into a cyclical conceptual model illustrating the relationships between informational inputs, cognitive processing, and behavioral feedback.
Results and Discussion:
Findings reveal that social media constructs specific cognitive representations of events by combining users’ cognitive biases, algorithmic prioritization of emotional content, and selective framing of reality. These representations do not merely reflect objective reality; rather, they reconstruct and simplify it.
The six core propositions of Cognitive Representation Theory are:
- Social media reconstructs reality rather than merely reflecting it.
- Confirmation bias and selective exposure reinforce preexisting beliefs.
- Algorithms and users’ network behaviors create and amplify echo chambers.
- Information overload increases cognitive load and promotes superficial processing.
- Emotional and identity-based prioritization intensifies affective polarization and a “us versus them” mentality.
- Framing and narrative construction steer users’ perceptions.
This process operates through a feedback cycle: algorithm-selected content merges with individual biases and emotions to create a specific mental representation. This representation guides the user’s media behavior, which in turn prompts algorithms to deliver similar content—thereby perpetuating and deepening the polarization cycle.
Analysis of events such as Iran’s 2021 presidential election and the 2022 protests demonstrates that this cycle can generate two or more “parallel realities” within a short period. This condition, by reducing intergroup interaction, hinders dialogue and fosters social distrust. To break this cycle, simultaneous interventions are recommended: at the micro level, cognitive media literacy education to raise users’ awareness of biases and encourage diversity in information sources; at the macro level, transparent regulation of algorithms and mechanisms for displaying a broader range of perspectives.
Conclusion:
Cognitive Representation Theory demonstrates that social media, through cognitive mechanisms and platform structures, reproduces reality and shapes users’ perceptions in a directional manner. By reinforcing unilateral mental frameworks, this process contributes to the intensification of political and social polarization. The proposed framework offers a basis for scientific analysis and policymaking in the realm of social media, emphasizing the necessity of educational initiatives, algorithmic regulation, and cognitive defense interventions.