The notion of popularity is prevalent within society. We have made charts of the most popular music and movies since the early part of the 20th century. Elections and referenda are primarily decided by who gets the most votes. Within computer systems, we monitor followers and endorsements in social networks, and track views, hits, and connection attempts in other networks.
Computationally, the problem of determining which items are popular appears at first a straightforward one. Given a dataset of votes, we can simply sort by the item identifier, then count up how many votes are assigned to each. When the number of votes is large, we might try to avoid the overhead of sorting, and aim to more directly pick out the most popular items with only a few passes through the data.
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