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Antonio Rinaldi

Not perfect neither complete (I'm only taking a buyer perspective), but:
1) manual solution: read reviews giving 1-2-3 stars foremost;
2) automatic solution: give each review a "genuineness" or "informativeness" score and compute review mean accordingly.
For example: consider the review poor if the mean number of stars given in the last 12 months / 10 purchases (potentially weighted by price) by the reviewer is very high or very small with no at all or very low variance. Really do we want to listen about an always-enthusiastic or always-whiny buyer? So a fake reviewer is caught quickly.
If it's too much to hope Amazon takes care, it is possible to build a browser addon to implement it.
In other words: try to fight bad data with data.

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