To be rational or sensitive? The gender difference in how textual environment cue and personal characteristics influence the sentiment expression on social media

Abstract

Online sentiments expressed by users play critical roles in various social media-based applications, and thus understanding the mechanism of what determines users expressing sentiment with different polarities bears strategic importance. Based on the affective response model (ARM), we develop a conceptual model about the determinants of users’ online sentiment polarity, from the cues of the textual environment from the target tweet and the user’s personal characteristics. Furthermore, the role of gender difference in these effects is also included. Empirical results indicated that users with higher social interactivity and positive historical sentiment expression are more likely to express positive sentiment towards online tweets with higher positive sentiment intensity. Females are more sensitive to the cue of textual environment, i.e, sentiment intensity, in the target tweets when expressing sentiments, while males are more rational when expressing online sentiment than females. Our study supplements the existing study on users’ online interaction behavior as rational and affective action by introducing a new way to study the driving behavior of sentiment expression.