In an article first published on The Conversation, NICK HAJLI and NICK JENNINGS look at how you can use AI to tell the fake from the real…
Before you buy something, or visit a new restaurant, or see a new film, you may be tempted to check out the online reviews. Researching what strangers think of the things we might like has become a familiar part of the modern consumer experience.
But how can we know which reviews to trust? Which ones are written by honest customers sharing their genuine experiences, and which ones are posted with ulterior motives?
PICTURE: cybrain/Shutterstock
For while consumer reviews can guide us towards the best products and services, concealed within the shadows are deceptive reviews, meticulously crafted to deceive and manipulate. Fake feedback, you might call it.
A negative fake review may be submitted by a competitor for example, hoping to cast doubt on the quality of a particular product. Or a positive sounding fake review may be designed by someone with a financial interest in a service to give it a dishonest boost in the market.
“A negative fake review may be submitted by a competitor for example, hoping to cast doubt on the quality of a particular product. Or a positive sounding fake review may be designed by someone with a financial interest in a service to give it a dishonest boost in the market.”
All of these can have a dramatic effect on a business’s public profile.
In 2023, the popular travel website Tripadvisor experienced a staggering influx of user-generated content, with more than 30 million reviews submitted by more than 17 million members. But within this vast sea of apparent customer feedback, 1.3 million reviews were flagged as fraudulent and subsequently removed.
Additionally, 33,194 businesses faced penalties for engaging in deceptive practices. And in the UK, government research has found that between 11 per cent to 15 per cent of reviews in specific product categories, such as consumer electronics and home and kitchenware, were thought to be fraudulent.
Cracking the code
To combat fake reviews, companies including Amazon have started using artificial intelligence to prevent the publication of hundreds of millions of potentially fraudulent reviews, ensuring the credibility of the platform.
But research suggests that there are quite a few things consumers can do to protect themselves.
Trust your instincts: When perusing reviews, rely on your intuition. Authentic feedback tends to strike a balance, presenting both positive and negative aspects of the product or service. If a review appears excessively positive or overly critical without substantiation, exercise caution.
Read between the lines: Pay attention to the language and tone used in reviews. Genuine feedback often sounds personal, reflecting the reviewer’s unique experience. Beware of reviews that seem generic, repetitive, or excessively promotional, as they may be deceptive endorsements.
Validate the source: Scrutinise the reviewer’s credentials to ascertain their credibility. Genuine reviewers typically furnish specific details about their interaction with the product or service, such as features, delivery timelines, or customer service encounters. Approach reviews which lack specific information with scepticism.
Look for patterns: Remain vigilant for anomalous patterns in reviews, such as sudden surges of positive or negative feedback within a brief time frame. These anomalies could indicate orchestrated attempts to manipulate ratings rather than genuine consumer experiences.
We rely on our readers to fund Sight's work - become a financial supporter today!
For more information, head to our Subscriber's page.
Review the reviewers
So in the same way that you may protect your computer from viruses, or stay alert to attempts to get hold of your personal information, it’s important to keep yourself updated on common methods used to deceive consumers. Well-known platforms such as Amazon and Tripadvisor usually offer guidelines for spotting fake feedback, while consumer advocacy groups and online forums dedicated to consumer awareness can provide valuable insights.
Websites and platforms also have a responsibility to make sure users are receiving trustworthy information. And advances in AI technology have introduced new tools that can assist in identifying and flagging potential fake reviews.
These AI-powered solutions play a critical role in preserving consumer trust and market integrity by using machine learning to analyse patterns and identify suspicious interactions in social media platforms.
Through investment in this kind of technology, companies can more effectively combat the spread of fake reviews and maintain the credibility of their review systems. They can also bolster trust and confidence in the authenticity of the reviews provided.
In a digital world, being able to differentiate between genuine feedback and deceptive endorsements is vital for making informed decisions. And if you do encounter a review you suspect to be fake, it’s always worth flagging it to the platform or website where it was posted. By alerting authorities, you’ll strengthen the integrity of online review systems – and help your fellow consumers make better decisions.
Nick Hajli is an AI strategist and professor of digital strategy at Loughborough University and Nick Jennings is vice-chancellor and president of Loughborough University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
