The internet is full of fake product reviews. Here’s what you can do to spot them


It’s a crime story fit for the digital age. It was recently reported that a number of restaurants in New York City were targeted by internet scammers who threatened to leave unfavorable “one-star” reviews if they did not receive gift certificates. Similar threats have been made to eateries in Chicago and San Francisco, and one vegan restaurant appears to have received eight one-star reviews in a week before appealing for money.

It’s surprising that something like this hasn’t come up before. Relying too much on the “wisdom of the crowd,” the way many people measure things by the approval of the rest of society, leaves us vulnerable to this kind of fraud.

It’s all about the numbers. Products and companies are measured online by the number of stars they receive on a five-star scale, influencers by the number of followers, and posts by the number of likes or retweets. The satirical Kardashian index provides a quantitative measure by comparing academics’ citations of research articles to the number of Twitter followers.

So why are these systems considered valuable and why do we consult them almost blindly? In an age of information overload, feedback and reputation systems enable quick decision making, giving us the feeling (or illusion) of being in control because the decision made is perceived to be informed.

A scarce commodity

Another idea here is the “attention economy paradigm.” According to this way of thinking, human attention is a scarce commodity and—as with all finite resources on this planet—has a high value.

Businesses are competing to get as high as possible on the first page of Google’s search results to get that attention. And user feedback is one of the many parameters that influence the hidden ranking algorithms of the search engine.

The remarkable success and acceptance of such reputation systems is based on the idea of ​​the wisdom of crowds. If one is asked to estimate something from a sufficiently large sample of the population, the average of these estimates is expected to be very close. actual value. Because any personal prejudices become irrelevant when they accumulate in large numbers.

But all systems that come with successful business models are open to abuse, and organized crime groups can attract opportunistic and malicious actors to the extent that they can create and systematically exploit such systems. For example, the business opportunities that emerged during the Covid-19 pandemic were immediately matched by a range of criminal activities, including shopping scams, disinformation, illegal broadcasting and even child sexual exploitation.

Fake reviews

There are several reasons and motivations for fake reviews. Business competitors may try to flood the business target with negative reviews to harm their competitors. Others may attempt to create positive reviews and misrepresent the quality of their products by creating fake profiles or “bribing” customers with free or discounted products.

But extortion with threats of negative feedback is particularly insidious. An increase in negative reviews on a business’s Google profile not only affects its search engine ranking, but also significantly affects potential customers’ purchasing decisions.

Although these practices are reported to have been simplified from organized groups in India, variations have been observed in other countries as well. Amazon recently sued 10,000 Facebook group administrators with more than 43,000 members for allegedly soliciting fake (positive) reviews in exchange for free products.

What can be done?

Abuse of online review and reputation systems has grown to epidemic proportions. The fight against it will require everyone’s coordination.

Google and other review and reputation service providers must devote more resources to preventing, detecting and removing fake reviews. Machine learning technologies have made impressive leaps in recent years and can help eliminate fake content.

Stricter rules governing the selection of reviewers ensure their participation under special conditions. We’ve seen this with verified buyer schemes that aim to guarantee that the reviewer has genuine experience with the business.

Feedback presentation, and in particular a star rating system, could have more contextual information, for example through additional color coding to convey sentiment extracted from textual comments. In this case, highly emotional comments based on less factual or useful information may have a different color than those that attempt to be unbiased and objective.

Businesses should also adopt a system for reporting problem reviews and use it responsibly. If negative reviews are genuine, they should not report them, as this affects the relationship with the feedback platform, which understandably creates more distrust of the business.

And consumers should be more vigilant and educated about it rather than following these rankings religiously. There are many signs of a fake look, including checking the language to see if they are common. It’s also instructive to check if a reviewer generates a large number of negative reviews on multiple and seemingly unrelated products in a short period of time.

We, the crowd, must be active participants in our buying experience by always being fair and recognizing and supporting the business when they exceed our expectations, as well as giving honest negative feedback and recommendations for improvement. Only then will the wisdom of the crowd truly serve us.

This article first appeared on The Conversation.





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