How would you detect it? Any detection algorithm that springs to mind seems easily defeatable. These devices are most likely all on individual pay-as-you-go cellular cards, each with their own iTunes account. Each review is probably either only a star rating, or for text-based reviews a randomly generated unique paragraph.
You could detect similar texts but that's just an arms race against new corpora being added to their generator.
Maybe detect the same app getting a lot of similar ratings in a period of time? But then the farm could just randomize the input list of apps among the farmers and stretch out the time period to make it look like more natural traffic.
I think that those kinds of things are necessary to fight spam. Gmail isn't great at detecting spam because there's some invincible algorithm invented 10 years ago that catches everything and hasn't changed. To block spam, Gmail is always adapting it's spam filtering bases on behavior of spammers.
I believe one would probably have to do the same thing to moderate app store rating.
Reviews are tied to app store accounts, which are tied to credit cards. Reviews also reset with each version of the app. You could detect the same accounts being used to review each version of the app, discount ratings from newly created accounts, discount ratings from accounts with reused credit cards, etc. It seems like an easier way to game the system would be to pay anyone with an iPhone $5 to download and rate your app.
You can have an app store account without a credit card. I don't think it was always possible, but it is now. Also, the accounts don't have to be newly created. This operation could be quite long-lived.
You could have some automated system which loads many different apps to be rated, so that the person in the picture isn't rating the same app over and over again in a short period of time.
