Why Amazon Reviewers Review (and How to Deal with Fake Reviews)

Dr Philip Wu | Senior LecturerDepartment of Digital Innovation and Management at Royal Holloway, University of London.

Online reviews have become an important phenomenon in this so-called reputation economy. Headlines such as “online reviews impact purchasing decisions for over 93% of consumers” seem exaggerated but not entirely surprising. On the surface, online reviews are simply after-sales opinions shared online by average consumers; yet, a close look would reveal that it’s a complex phenomenon influencing, and being influenced by, commercial activities. Most research about online reviews, including two of my own (1 & 2), focused on the value (e.g., “helpfulness”) and impact (e.g., sales) of the reviews, whereas the people who contributed those reviews have largely been overlooked. After all, who are these reviewers and why are they writing product reviews?

These are important questions not only for social scientists who are interested in studying the reviewing behaviour, but also for today’s e-commerce platforms where fake reviews are rampaging. Thus, in a more recent paper, I turned my attention to reviewers on Amazon to explore how a mix of, and the interaction between, different types of motivation shape the reviewers’ behaviours. The theoretical foundation of the work was the theory of motivation crowding, which posits that the motivational interaction in performing a task can result in motivation moving toward the extrinsic side (crowding-out) or the intrinsic side (crowding-in).

I conducted in-depth interviews with 27 reviewers on Amazon.co.uk, including four Top 10 reviewers at the time and six reviewers in the “Hall of Fame”, plus a six-month observation of the Amazon reviewer forums (in writing this blog post, I discovered that these forums have now disappeared! I think I know why.). I use the interviewees’ own words to explain the four dominant motives for writing product reviews on Amazon:

  • enjoyment (intrinsic) – “I enjoy reviewing”
  • material reward (extrinsic) – “I write reviews so I can get freebies”
  • reputation/recognition (extrinsic) – “I need some kind of recognition”
  • direct reciprocity (extrinsic) – “You got the obligation coz you agreed to review”

More interestingly, there is a crowding-in effect where reputation (commensurated as reviewer league table ranking) reinforces the enjoyment of reviewing, and a crowding-out effect where the obligation of reciprocating material reward undermines the enjoyment.  I also found that the reviewers’ motivation mix could evolve as their rankings change. Many prolific reviewers started reviewing with an intrinsic motivation of “fun” or enjoyment. As the reviewing activity is being rewarded by status recognition and unsolicited freebies, extrinsic elements become more prominent in the motivation mix. After a while, however, the reviewers begin to feel a loss of self-determination due to external influences and decide to “take a step back” from pursuing extrinsic rewards, which result in intrinsic interest taking centre stage again.

The motivation crowding effects and the evolution of motivation mix have important implications for e-commerce platforms like Amazon.  For example, for novice reviewers, positive feedback (in the form of “helpful” votes) can create a powerful “recognition-enjoyment” crowding-in effect. Hence, the platforms need proper presentation and sorting mechanisms to ensure visibility of new reviewer’s contribution so as to curb the detrimental Matthew effect.

The study also raises questions about e-commerce platforms’ strategies in dealing with “fake reviews”. Some claim that they have solved the problem through automated fake review detecting (e.g., Fakespot). Fake reviews are generally understood as reviews written by people who did not actually purchase the product or service. However, as review writing is driven by a whole range of interacting motives, we need to have a more nuanced view of what fake reviews really are. Many of the prolific reviewers I interviewed had accepted “freebies” but also produced honest and high-quality reviews.

Perhaps one way to combat fake reviews is through some sort of grassroots review moderation.  I was fascinated when a seasoned reviewer told me that he acted like a “warrior” to fight against fake reviews and he knew which reviews were fake at first glance. He would vote the fake review “unhelpful”, report it to Amazon, or even write a review pointing out why the other review was fake. These “warriors” seem motivated either by a commitment to the platform or a moral duty of “making things right.” Leveraging the motivation of this small group of individuals, coupled with an automated detection system, could be the key to solving the fake review problem.

Dr Philip Wu is a Senior Lecturer in the Department of Digital Innovation and Management at Royal Holloway. His research lies at the intersection of social psychology, technology design, and information management.

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