[Paper Review] Why Does Hyper-Personalized Short-Form Advertising Exhaust Us?

Paper: Impact of Short-Form AI Recommendation Algorithm Characteristics on Ad Fatigue and Ad Avoidance: Focused on Confirmation Bias, Perceived Intrusiveness, Algorithm Trust, and Perceived Optimization (Kim Na-kyoung, 2025). Key finding: ad fatigue is statistically proven as the absolute cause (β=1.219) of ad avoidance — the most powerful driver. Intrusiveness as the strongest driver of fatigue: ads that violently interrupt viewing context (appearing mid-video, breaking viewing rhythm) are the primary cause of fatigue regardless of relevance or personalization quality. Surprising finding: confirmation bias (seeing ads consistent with existing beliefs/preferences) actually significantly reduces ad fatigue — the familiar and expected feels less intrusive than the algorithmically "optimized" but unexpected. Algorithm trust as buffer: users who perceive the platform''s recommendation method as fair and transparent are more likely to accept ads as "valuable information" rather than spam; the transparent explanation of "why this ad is shown to you" matters significantly. Implications for marketers and platform designers: (1) Moving beyond accuracy competition to designing naturalness of user experience; (2) Providing cognitive comfort through familiarity (confirmation bias) rather than maximizing precision targeting; (3) Approaching through native methods that don''t break immersion; (4) Building trust through transparent explanation. The core insight: hyper-personalization can backfire — the precision that makes targeting feel "eerily accurate" also makes it feel intrusive; the most effective short-form advertising creates the sensation of appearing naturally within the user''s content flow rather than being injected by an algorithm that knows too much.