From Influence to Action: Decoding Short-Video Travel Influencers’ Impact via Text Mining and SEM-Based Sequential Mediation

• Kai Liao,
• Rui Liang,
• Zi-yang Liu,

Vol. 19, No. 9, September 30, 2025
10.3837/tiis.2025.09.002, Download Paper (Free):

• Short-video platforms
• text-mining
• Sequential mediation
• Tourist behavior
• Travel influencers

Abstract

Background: Travel influencer-tourist interactions on short-video platforms significantly shape travel behavior, yet their cognitive and affective mechanisms remain underexplored. Objectives: Grounded in Self-Categorization Theory (SCT), this study investigates how travel influencers affect tourist behavior on Chinese short-video travel platforms, with specific objectives: (1) To identify key influencer-perceived dimensions (inspiration, trust, attraction) and psychological mediators (self-categorization, emotional commitment, self-worth); (2) To develop a model illustrating cognitive and affective mediation pathways; (3) To empirically test these mediations. Methods: Employing a mixed-methods design, text-mining and structural equation modeling (SEM). Results: (1) Perceived inspiration and trust influenced tourist behavior via self-categorization; (2) Emotional commitment and self-worth further mediated the self-categorization-behavior relationship; (3) Perceived attraction was rejected, due to content homogenization case by insufficient cultural depth and authentic narratives. Conclusions: (1) Extends SCT to influencer-driven travel behavior on short-video platforms, revealing the sequential mediation of cognitive (self-categorization) and affective (emotional commitment, self-worth) factors; (2) Integrates text-mining with SEM validation; (3) Advocate for authentic, culturally embedded content to foster inspiration and trust, countering homogenization trends in influencer marketing.

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