Consider a recommendation system $($e$.$g$.,$ Netflix$).$ Suppose that there is a malicious user with $10,000$ fake email addresses. The user creates $10,000$ Netflix accounts, and each account has the same user characteristics $($same age, gender, likes, and dislikes$).$ However, each fake user provides contradictory movie reviews. For example, a given fake user may claim to like Romantic Comedy films, but it rates $50$ First Dates$($a Romantic Comedy$)1$ out of $5$ stars, whereas it rates $$The Joker$($an Action Thriller$)5$ out of $5$ stars.

What effect might this have on the recommendation system?