Catching eyes of social media wanderers: How pictorial and textual cues in visitor-generated content shape users’ cognitive-affective psychology

Documenting and sharing individual museum visits flourishes on social media. However, little research exists about how peer-generated content cues shape prospective visitors' perceptions and decisions. Drawing upon the stimulus‒organism‒response (SOR) framework, we holistically investigated the visual weight and attitudinal feedback of exhibition selfies and caption appeal types via eye-tracking technology and interviews, as well as the persuasive execution of accompanying texts using an experimental method. Two sequential studies were conducted: Study 1 empirically investigated the superiority of selfies and emotional titles in attracting visual attention and their influence on viewers' attitudinal evaluations through aesthetic judgments, mental imagery and flow experience during visual processing; Study 2 differentiated two types of textual stimuli (informational self-disclosure and emotional self-disclosure) that indirectly influence viewers’ behavioral intention through their inner organism changes in aesthetic experience and trust. The findings provide theoretical and marketing insights for tourism and cultural organizations to promote their social media communication.     

Detection of potential customers’ empathy behavior towards customers' reviews

The aim of the current study is to identify potential customers' empathy behavior and their behavioral reactions based on appraisal and stimulus–organism–response (SOR) theories to customers' reviews of financial services firms using lexicon-based unsupervised learning techniques. After filtering, we obtained 30263 reviews from the Yelp dataset of financial service companies. We examined the connections between several sorts of emotional dimensions and different types of behavioral reactions of potential consumers using lexicon-based unsupervised machine learning methods. Our findings show that the various types of customer sentiment have a significant impact on potential customers' emotional experiences on social media platforms, prompting them to behave differently. Furthermore, potential consumers' reactions to the customers' reviews varied according to their seven emotional aspects. The study is the first to examine the impact of potential customers' empathetic behavioral reactions on customers' evaluations using lexicon-based unsupervised learning techniques.