For example, shopping around to find the cheapest price for something has become far easier.
The first page of results – those with the highest scores – consisted almost entirely of little-known brands, with nearly 90 per cent of the reviews from unverified buyers.
In other words, there was no evidence that the reviewer had ever bought the item in the first place.
A flurry of very good posts for a less well-known brand is one of the classic footprints which enable fake reviews to be identified.
Ever since then, a complicated evolutionary game has been played between the spammers and the spam filters.
It is a game because spam wins if it gets through, and the filters win if it does not.