Jeffrey K. Lee’s research while affiliated with American University and other places

This paper suggests a theory-driven approach to address the managerial problem of distinguishing between real and fake reviews. Building on memory research and linguistics, we predict that when recollecting an authentic experience in a product review, people rely to a greater extent on episodic memory. By contrast, when writing a fictitious review, people do not have episodic memory available to them. Therefore, they must rely to a greater extent on semantic memory. We suggest that reliance on these different memory types is reflected in the language used in authentic and fictitious reviews. We develop predictions about five linguistic features characterizing authentic versus fictitious reviews. We test our predictions via a multi-method approach, combining computational linguistics, experimental design, and machine learning. We employ a large-scale experiment to derive a dataset of reviews, as well as two datasets containing reviews from online platforms. We also test whether an algorithm relying on our theory-driven linguistic features is context-independent, relative to other benchmark algorithms, and shows better cross-domain performance when tested across datasets. By developing a theory that extends memory and psycholinguistics research to the realm of word of mouth, this work contributes to our understanding of how authentic and fictitious reviews are created.

This paper explores the idea that consumer influencers can shape reference group meanings in social media. Through a survey in which over 5,000 participants provided open-ended reference group associations for 25 major brands, the authors find that social media influencers can either strengthen or change brand reference group associations. Specifically, the typicality of the influencer (relative to a brand's stereotypical consumer) can shape ideas about the perceived homogeneity of the brand’s consumers, which ultimately influences the strength and tightness of brand associations. This research combines seminal theories regarding cultural and sociological influences on branding, concepts relating to stereotype change, and a multi-method approach to assess new digital flows of cultural meaning from consumer influencers to brands.

Every day, consumers share word of mouth (WOM) on how products and behaviors are commonly adopted through the use of consensus language. Consensus language refers to words and expressions that suggest general agreement among a group of people regarding an opinion, product, or behavior (e.g., “everyone likes this movie”). In a series of online and field experiments, the authors demonstrate that the interpretation and persuasiveness of consensus language depends on the tie strength between the communicator and the receiver of WOM. Although abundant literature highlights the advantage of strong ties (e.g., close friends, family) in influence and persuasion, the authors find that weak ties (e.g., distant friends, acquaintances) are more influential than strong ties when using consensus language. The authors theorize and demonstrate that this effect occurs because weak ties evoke perceptions of a larger and more diverse group in consensus, which signals greater validity for the issue at hand. These findings contribute to research on WOM, tie strength, and descriptive norms and provide practical implications for marketers on ways to analyze and encourage consumer discourse.