후원 여부에 따른 유튜브 스마트폰 리뷰의 메시지 차이: 단어 네트워크 기반 분석 = Analyzing Message Differences in YouTube Smartphone Reviews by Sponsorship: A Word Network Approach

다국어 초록 (Multilingual Abstract)

Influencer marketing has become a critical driver of consumer decision-making, particularly on social media platforms such as YouTube. Sponsored disclosures are known to affect consumer trust and attitudes, yet relatively little research has examined how sponsorship alters the actual content and message structures of influencer reviews. This study aims to investigate message differences between sponsored and non-sponsored YouTube smartphone reviews by analyzing iPhone 16 and Galaxy S24 videos. Drawing on corporate promotional videos, sponsored influencer reviews, and organic user reviews, the research applies multiple text mining and word network techniques to compare linguistic patterns, thematic emphasis, and structural similarity to corporate messaging. The results indicate that sponsored reviews place greater emphasis on technical features such as camera specifications and AI capabilities, whereas non-sponsored reviews highlight user experiences, practicality, and performance. Moreover, similarity analysis demonstrates that sponsored reviews are more closely aligned with corporate promotional content than non-sponsored reviews. These findings reveal that sponsorship not only influences consumer perceptions but also shapes the content strategies of influencers at the message level. The study contributes to influencer marketing literature by extending content analysis with advanced computational methods and provides practical implications for firms and influencers seeking to balance transparency, differentiation, and authenticity in sponsored content.