Dynamics of Firm-Consumer Interactions on Social Media Platforms
(A2022-107698)

AUTHORS

Saehoon Chang, Queen's University; Ceren Kolsarici, Queen's University

ABSTRACT

Effective management of consumer engagement using firm-generated content on social media is vital for creating positive brand impressions to build brand loyalty. However, even as firms engage consumers on social media platforms, it is unclear why certain messages receive more positive outcomes from consumers with high likes and shares and others do not. We build on the extant theoretical work on social exchange theory, dual-process theory, elaboration likelihood model, and contextual empathy, we empirically investigate the dynamics of firm-to-consumer interactions on social media platforms. Using sentiment & content analysis techniques and multiple regularization processes (LASSO, SCAD, MCP) and Twitter as a context, we investigate i) which message content characteristics lead to different levels of consumer engagement and ii) how these change throughout the dynamics of the interaction as we move from firm-to-many to firm-to-one communication. The results suggest, among other things, that emotional content in mass communication and precision and clarity of the message in individual attention lead to higher likes and retweets.