Background:
The rapid growth of social media has transformed the landscape of information consumption and dissemination worldwide. In countries like Iran, where traditional media are often state-controlled and public trust in official sources may be limited, social media platforms such as Telegram, Instagram, and X (formerly Twitter) have emerged as alternative channels for news, opinion, and social discourse. However, this transformation has brought with it a serious challenge: the widespread circulation of fake news and misleading information, often disguised in forms similar to credible content. As users increasingly rely on these platforms for real-time updates, distinguishing fact from fiction becomes difficult, and misinformation can spread quickly, influencing public opinion, behavior, and even social stability.
Objective:
The primary objective of this study is twofold: first, to identify and categorize the structural features that differentiate fake information from real information on Persian-language social media platforms; and second, to investigate how these structural features affect the sharing behavior of Iranian users. The study seeks to move beyond content verification and explore how form, presentation, and rhetorical structure shape users' perceptions and actions, especially in emotionally or politically sensitive contexts.
Methodology:
A mixed-methods research design was employed. In the first phase, a qualitative content analysis was conducted on a corpus of social media posts that were previously verified as either fake or real. These samples were analyzed to extract recurring structural elements, including headline style, emotional tone, source attribution, use of visuals, narrative coherence, and rhetorical strategy. In the second phase, a survey was distributed among a diverse sample of Iranian social media users to quantitatively assess how these structural features influence users' likelihood of sharing, liking, or engaging with content. The survey included scenario-based questions, self-report scales, and demographic variables to account for contextual factors such as age, education, and media literacy.
Findings:
The findings reveal a clear distinction between the structural composition of fake and real information. Fake content tends to rely heavily on emotional triggers, hyperbolic language, fear-based appeals, and the illusion of credibility through repetition or pseudo-expert citation. Such content is often narrative-driven, lacking in verifiable data, yet highly persuasive due to its affective tone and simplified storytelling. In contrast, real information is generally structured with a focus on factual integrity, consistency, citation of credible sources, and a more neutral or balanced tone. However, the study found that structural sophistication alone does not guarantee user skepticism. Users are significantly more likely to share fake information if it aligns with their emotional state, existing beliefs, or perceived social urgency—even when the content lacks credible backing. This behavioral pattern underscores the role of cognitive bias and affective influence in digital information sharing.
Conclusion:
The study demonstrates that the structure of information—its presentation, tone, and rhetorical form—plays a critical role in users' decision to engage with and redistribute content on social media. This influence often outweighs factual accuracy, especially in fast-paced, emotionally charged digital environments. Recognizing and addressing these structural cues is essential for developing effective strategies to curb the spread of misinformation.
Implications:
The research offers valuable insights for media policymakers, platform developers, educators, and fact-checking organizations. It highlights the need for structural awareness training in digital literacy programs and suggests that content moderation efforts should not focus solely on verifying facts but also on identifying high-risk structural features. Moreover, the study recommends that social media platforms implement design-based nudges and contextual warnings that alert users to emotionally manipulative structures in content, thus encouraging more deliberate sharing practices.
Keywords:
Social Media, Information Structure, Fake News, Sharing Behavior, Iranian Users.