The “100,000+ Clicks” Dream Comes True: A Study on the Click-and-Read Behavior of WeChat Tweets From the Perspective of Emotional Expression

An in-depth and refined empirical study on the emotional expression of information and the information processing mechanism of audiences is carried out to provide enterprises and other organizations with insights and references as regard to the effective utilization of WeChat Tweets for information dissemination and marketing purposes. Based on 1,465 actual tweets from two different types of WeChat public accounts (knowledge communication and information releasing), this paper applies the limited attention capacity model and the signaling theory to analyze the influence of emotional presence, emotional complexity, emotional intensity, and emotional polarity of tweet titles on the click-and-read behavior of the audience. The results show that for WeChat public accounts serving the purpose of knowledge communication, emotional presence and emotional complexity of tweet titles, as well as the emotional intensity of positive tweet titles, has no significant effect on the click-and-read behaviors of the audience. Besides, the emotional intensity of negative tweet titles has a significant negative impact on the audience’s click-and-read behaviors. While for WeChat public accounts serving the purpose of information releasing, tweet titles with emotional presence and lower level of emotional complexity are more likely to trigger click-and-read behaviors of audiences; emotional intensity of negative tweet titles has no significant effect on the click-and-read behaviors of audiences, and emotional intensity of positive tweet titles has a significant negative impact on the audience’s click-and-read behaviors. Thus, this study further analyzes the influence of emotional factors, such as emotional existence, emotional complexity, emotional intensity, and emotional polarity of tweet titles on the click-and-read behavior of consumers and further explores the emotional information processing mechanism of WeChat tweet readers.