Mapping Influencers: Understanding Public Discourse on Hotel Robotics Through Social Network Analysis

Abstract

The rapid deployment of robotics in the tourism and hospitality industry has sparked intense discussions on social media. This study applies diffusion of innovation theory and two-step flow theory to examine the types of influencers on hotel robotics, their roles in information flow, and their sentiments on the topic. Using a dataset of 16,269 tweets, the study employs social network, thematic, and sentiment analyses to analyze the data. The findings identify five types of influencers: technology experts, technology businesses, media, tourism and hospitality businesses, and nano influencers. Different types of influencers serve different informational roles within social networks and exhibit varying emotional tendencies in their content. The findings help reinterpret adopter categories based on social network roles, highlighting the applicability of the two-step flow theory in social media environments. The findings offer strategic insights for hotel operators on leveraging social media for effective marketing and optimizing robot deployment.