Paper Type

Short

Paper Number

PACIS2026-1788

Description

Social media spoilers are increasingly shaped by platform affordances, algorithmic curation, and real-time participation rather than by interpersonal etiquette alone. This study develops a dual-lens framework integrating involvement theory and the SMILE model to examine how users cognitively and affectively respond to spoiler exposure on social media. The study conceptualizes spoiler encounters as cognitively appraised disruption events involving spoiler sensitivity, perceived severity, and perceived control, alongside emotional responses of anger and anxiety. Media form and timeliness are further proposed as contextual moderators shaping these relationships. An explanatory sequential mixed-methods design is adopted, combining a controlled online experiment with semi-structured interviews. The study contributes to research on social media literacy, platform governance, and algorithmic mediation by explaining why identical spoiler content may generate divergent reactions across users and release contexts.

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13-Design

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Jul 5th, 12:00 AM

Involvement and the SMILE Model: A Dual-Lens Framework for Social Media Spoilers

Social media spoilers are increasingly shaped by platform affordances, algorithmic curation, and real-time participation rather than by interpersonal etiquette alone. This study develops a dual-lens framework integrating involvement theory and the SMILE model to examine how users cognitively and affectively respond to spoiler exposure on social media. The study conceptualizes spoiler encounters as cognitively appraised disruption events involving spoiler sensitivity, perceived severity, and perceived control, alongside emotional responses of anger and anxiety. Media form and timeliness are further proposed as contextual moderators shaping these relationships. An explanatory sequential mixed-methods design is adopted, combining a controlled online experiment with semi-structured interviews. The study contributes to research on social media literacy, platform governance, and algorithmic mediation by explaining why identical spoiler content may generate divergent reactions across users and release contexts.