Consumers seek organic reviews of products and services (organic eWOM) to verify whether they made the right choice (Erkan and Evans, 2016). However, the authenticity of brand promotion (e.g., blurred boundary advertisement) hinders consumers’ decision making. Consumers are calling for transparency of information between social platforms and users. This study is to develop efficient models to distinguish blurred boundary advertisements from organic eWOM. Drawing upon dual-process theory, we developed logistic models which can distinguish blurred boundary advertisements from organic eWOM in social media marketing platforms with decent explanations. Blurred boundary advertisement can be detected by features about posts, comments, bloggers and followers. Moreover, number of followers, number of posts and number of comments showed U- shape relationships with detecting blurred boundary advertisement. With more accurate statistical and machine learning-based models, this study helps consumers and platforms solve possible fairness issues in digital marketing.
Liu, Lu; Liu, Libo; and Xiao, Yundan, "Detecting Blurred Boundary Advertisement in Social Media Marketing Platform" (2022). PACIS 2022 Proceedings. 42.
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