Spektrum Iran

AI as a Boundary Object: The Persian X Discourse

Articles in Press

Document Type : Original Research Paper

Author

Shaho Sabbar

Department of Iranian Studies, Faculty of World Studies, University of Tehran, Tehran, Iran.

10.22034/spektrum.2026.569202.1059
Abstract
This study investigates how Persian-speaking users on the social media platform X engage with generative artificial intelligence as a sociotechnical and discursive phenomenon. Drawing on a dataset of 24,215 Persian-language posts, we employ a multi-label topic modeling framework and affective profiling to analyze public discourse surrounding AI tools, their perceived implications, and normative judgments about their use. Rather than treating sentiment as a static indicator of opinion, we interpret affective expression as a communicative act shaped by platform incentives and cultural context. Our findings show that AI is positioned not only as a technical artifact but as a boundary object entangled with debates over expertise, ethics, and institutional legitimacy. The discourse is anchored in practical concerns—especially labor, education, and tool comparisons—but frequently extends into culturally specific narratives about risk, fairness, and epistemic authority. Emotionally, the conversation is marked by pragmatic positivity, critical intensity, and a sizable neutral band reflecting orientation rather than evaluation. This study contributes to ongoing debates in communication, AI ethics, and platform studies by offering a non-Anglophone, culturally grounded analysis of how publics perform vernacular governance over emerging technologies. Emotionally, the conversation is marked by pragmatic positivity, critical intensity, and a sizable neutral band reflecting orientation rather than evaluation. This study contributes to ongoing debates in communication, AI ethics, and platform studies by offering a non-Anglophone, culturally grounded analysis of how publics perform vernacular governance over emerging technologies. Drawing on a dataset of 24,215 Persian-language posts, we employ a multi-label topic modeling framework and affective profiling to analyze public discourse surrounding AI tools, their perceived implications, and normative judgments about their use.

Keywords: artificial intelligence; sentiment analysis; digital publics; vernacular governance; Persian discourseKeywords: artificial intelligence; sentiment analysis; digital publics; vernacular governance; Persian discourse

Keywords

artificial intelligence
sentiment analysis
digital publics
vernacular governance
Persian discourse

Subjects

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