Social media, especially Twitter, has become an important platform for Online Travel Agents (OTAs) such as Traveloka, Tiket.com , Agoda, and Booking.com to engage with customers and manage their brand reputation. However, traditional engagement metrics are less able to capture the complex dynamics of social networks. This study aims to develop a hybrid framework combining Social Network Analysis (SNA) and Artificial Neural Networks (ANN) to evaluate user influence more comprehensively. By integrating centrality metrics with engagement data, the proposed method generates actionable influence scores. The results show that Traveloka and Tiket.com leverage strong centrality and cohesive networks, while Agoda focuses on grassroots engagement and Booking.com relies on authentic and user-driven promotions. The ANN-based approach enables OTAs to identify key influencers, foster cross-community interactions, and optimize social media strategies for competitive advantage in the travel sector.