The importance and influence of online shopping goes without saying these days. As consumers turn to the internet’s retailers for everything from groceries to home furniture, it becomes even more important to know how to recognize quality products without seeing the item until it’s at their front door. Online shoppers often turn to reviews for answers on if something’s worth buying; on the surface, reading the thoughts of people who have purchased the same product serves as the digital version of a word-of-mouth recommendation. Unfortunately, some sellers take advantage of the review system by using fake reviews to inflate their star ratings and convince buyers that they’ll receive a better product than they actually will.
So, if a shopper can’t rely on reviews to tell the whole story, how can they be discerning in their online purchases? As Kogod professor of marketing Jeffrey Lee explains in his recently published research, certain language patterns can indicate that a review is fake. Taking note of those patterns can help people recognize when they’re reading somebody’s actual opinion or a hidden advertisement.
Lee’s paper, “Been There, Done That: How Episodic and Semantic Memory Affects the Language of Authentic and Fictitious Reviews,” approaches the topic of fake reviews through a psychological, theory-driven lens, which he hopes brings a fresh perspective to a conversation that has been ongoing for years. “When we started our research in 2017, fake reviews were already a big problem. However, what struck us was that most ideas were looking at which algorithms or data features could predict these reviews,” he recalled. “When we tried to amalgamate the insights across ideas and fields, it became challenging to make sense of them since they often contradicted each other. We hope our angle, which differs slightly from most, adds a valuable perspective.”
Lee and his coauthors centered the research around their prediction that fake reviews could be identified by the language they use. Where a genuine reviewer often draws upon their experiences with the product to explain why they like or dislike it, false reviewers don’t have that experience to reference. As a result, Lee explained, fake reviews tend to be vague.