How emotional expression in human-like virtual influencers drives user engagement: empathy model and its antecedents

Introduction: This study builds upon the rapid advancement of artificial intelligence and influencer marketing to examine the impact of emotional expressions by human-like virtual influencers on user engagement. Utilizing the empathy model and its antecedents, it investigates how users' perceptions-specifically perceived attractiveness, authenticity, escapism, and presence-affect both cognitive and affective empathy, which, in turn, influence user engagement. Methods: A within-subjects experimental design was employed to test the proposed model. The study involved 118 participants who were exposed to six distinct emotional stimuli exhibited by virtual influencers. Results: The findings reveal significant linear effects of perceived authenticity and presence on both cognitive and affective empathy. Moreover, perceived attractiveness and escapism were found to jointly enhance users' cognitive and affective empathy. The study also uncovers mediating effects of cognitive and affective empathy on user engagement. Subgroup analysis highlights the considerable impact of human-like virtual influencers' emotional expressions, particularly positive emotions, on user perceptions and empathy. Conversely, extreme negative emotions, such as anger, were found to reduce empathy through the perception of escapism. Discussion: These results contribute to a deeper understanding of the mechanisms driving user engagement with human-like virtual influencers and suggest strategies for enhancing engagement through emotional expression. The study provides valuable insights for the design and implementation of virtual influencers in marketing strategies, emphasizing the critical role of emotional expression in fostering meaningful user connections.