With increased competition, the digital market like Amazon, Twitter and Facebook is flooded with fake reviews and fake accounts.
The web is filled with Reviews. With the increase in competition amongst the big tech giants, the one thing that compels the customer to buy a product are the reviews. Not only does these reviews, make customers positive about a product but it also substantiates the quality of the product.
Similarly increase in number of likes, comments, and tweets in Twitter, Facebook or any other social media platform respectively give away a positive outlook towards the person's profile. People are somehow compel to buy products or services, that have higher reviews because they feel safe with it, not to mention they feel the accountability with the product. People are often able to see posts having more retweets, likes, and comments on their social media feed, because the algorithm governing social media platforms are designed to make such posts visible.
As per a research done by the investigative agency Which? 97% of the shoppers rely on online reviews for make a purchase. Another report by Britain's competition and Market Authority estimates that almost US$30 billion spending is influenced by online reviews.
However, in this digital world, of plethora of reviews and likes, it is extremely hard to segregate the authenticate from fake. What is often visible and comprehended as the positive review for any product could be a fake account handling it. A study, "The Market For Fake Reviews", states that chances of sale of a product can be increased by 380% as a result of the online review.
An investigative reporting agency Which? carried out an investigation regarding the tech gadgets sold on Amazon. The agency investigated 14 tech products like headphones, smart watches and wearable devices. The first page of these gadgets had five-start reviews for 71% of the items, but interestingly, 90% of the reviews were unverified.
This is not the first time that Amazon's digital space has been criticised for flouting fake reviews. In the above mentioned study, which was conducted by UCLA and UCA, it is revealed that in order to gain positive reviews, Facebook serves as the platform for Amazon in recruiting fake reviewers.
The study states that, "To do so, Amazon sellers create Facebook private groups where they promote their products by soliciting users to purchase their products and leave a five-star review in exchange for a full refund and in some cases an additional payment."
Between March 28, 2019 to July 2019, the researchers were able to identify 23 fake review related groups everyday, with 16000 members on an average and 568 fake review solicitation posted per day. The study observed that the payment was usually with paypal, and 15% of products offered a commission that can refund the cost of the product.
Another finding of the study was that most of the products started generating fake reviews after 156 days and 229 days respectively, which indicated that the reviews were generated after the products were older.
The study finds with the help of fake reviews, the average product rating can be increased by about 5% from 4.3 stars to 4.5 stars.
Interestingly Facebook launched a legal group for identifying the companies selling fake likes and reviews on march 2019.
In an investigation, The Newyork Times about the fake factory flouting around the social media. The report investigated a company Devumi, which was selling Twitter followers and shadowy global marketplace in Social media Fraud. The report found that the company has provided customers with more than 200 million twitter followers, with 3.5 automated accounts.
Another research study done by University of California and University of Indiana, states that 48% of the accounts are not people. The study, "Online Human-Bot Interactions: Detection, Estimation and Characterization", states that between 9% and 15% of the twitter users are bots.
The study mentions Machine learning technique that can be used for identifying the bots, The attributes of this technique are: users and friends meta-data, tweet content and sentiment, network patterns, and activity time series .The study classified almost 14M accounts between human accounts and bot accounts.
Experts believe that the issue of fake accounts, reviews and likes can easily be tackled by applying Machine learning algorithm. However, as the companies are more focused in making big money, they often ignore the potential threat generated to the users life because of fake reviews or fake likes.
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