Thank you for being a Fakespot user. I thought I'd bring in some perspective to your question.
Your observation of the preponderance of unreliable reviews on Amazon matches what we see across the board.
Unfortunately, ever since Amazon opened up to 3rd party sellers, the reviews have become a marketing tool by a lot of these sellers to move ahead of other products. These sellers use everything from pure fake reviews to gamed verified purchase reviews. This is major reason why so many reviews nowadays are unreliable, it is truly a wild west out there in the eCommerce world and fake reviews can mean $$$.
With that said, we just launched Fakespot Guardian as part of our new Chrome extension which solves the 3rd party seller problem by telling you if a seller is reliable or not. By knowing if seller and reviews are reliable, you will be able to purchase anything with confidence.
We have been bootstrapped and funded by institutional investors that allows us to function freely from being in the "unnamed but big review website starting with Y" business model. Ethically speaking, I personally would never support that as it goes against our mission as a company and what we are aiming to build here.
We actually get consistent DDoS attacks which are coming from angry e-Commerce sellers that have dismal grades on Fakespot, and that is occurring ever more frequently.
And from our internal research at Fakespot, we concur. The positivity bias from influenced reviews such as the Vine review program and multitudes others is rampant.
Our ML based algorithms will penalize any biased reviews and show case them to our users.
Hi, Saoud from Fakespot here. My co-founders and I all got scammed and duped by fake reviews and Fakespot was built to bring back trust and transparency to the e-commerce experience (and others).
We have a strict policy to remain neutral in our analyses and we do not in any way, shape or form accept bribes or copt partnerships.
Fakespot CTO here. That's a good observation. Our engines utilize NLP heavily conjoined with proprietary ML models to detect influenced reviews that basic statistical analysis will never (or with low levels of success) be able to infer from review data sets, unless there are very basic signals such as 100 5-star reviews posted in an hour.
Fake review authors and providers are increasingly becoming sophisticated to bypass various filters in place on Amazon and other websites so you need to be able to leverage SOTA analysis to detect them. We also don't reveal how we detect certain fake reviews due to the fact that they will use that information to their advantage to further exploit our system, which allows us to be a couple steps ahead.
Anyone interested to know more about this topic feel free to email me at [email protected].
One of the main authors was compensated by the largest coffee retailer in Germany.