Mining brand value propositions on Twitter: exploring the link between marketer-generated content and eWOM outcomes

Abstract Content marketing has become a mainstream channel for brands to engage the market with value propositions. Through content, control, instigate and co-create its target audience. However, nature of propositions embedded within cycle content co-creation their impact on eWOM outcomes received scant attention from an empirical perspective. In this paper, we propose proposition-based framework around using established business perspectives. We employ bidirectional Twitter data customers unearth descriptive, diagnostic predictive insights into Using sample marketer- user-generated 10 Coffee ( n (MGC) = 290, (UGC) 8811) Car 635, 7035) in 2018, taxonomy based literature was proposed validated. The results our study identify (a) descriptive explaining differentiation brand propositions, (b) relating consumer sentiments response proposition mix (c) models predicting brand-specific values’ influencing Like, Share, Comment Positive/Negative valence. Our show that effective social media strategy selectively uses elements (i.e. 4 P’s) attract favourable outcomes.