Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.

Abstract: Selecting an advertisement is disclosed. A preference event associated with a first advertisement is received from a first user. A quality score for the first advertisement is determined based at least in part on the received preference event. An advertisement fulfillment request is received. The request is responded to by selecting an advertisement based at least in part on the quality score of the first advertisement.

Abstract: Promoting a candidate content item included in a plurality of content items is disclosed. A preference event by the first user is detected. A plurality of user reputation scores is received. For the candidate content item in the plurality of candidate content items, a content reputation score is determined based at least in part on a portion of the received user reputation scores. A determination of whether to promote the candidate content item is made based at least in part on the content reputation score. The candidate content item is promoted if it is determined that the candidate content item should be promoted.

Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.

Abstract: Promoting a candidate content item included in a plurality of content items is disclosed. A plurality of user reputation scores is received. For the candidate content item in the plurality of candidate content items, a content reputation score is determined based at least in part on a portion of the received user reputation scores. A determination of whether to promote the candidate content item is made based at least in part on the content reputation score. The candidate content item is promoted if it is determined that the candidate content item should be promoted.

Abstract: Promoting a candidate content item included in a plurality of content items is disclosed. A plurality of user reputation scores is received. For the candidate content item in the plurality of candidate content items, a content reputation score is determined based at least in part on a portion of the received user reputation scores. A determination of whether to promote the candidate content item is made based at least in part on the content reputation score and a dynamically adjusted threshold. The candidate content item is promoted if it is determined that the candidate content item should be promoted.

Abstract: Selecting an advertisement is disclosed. A preference event associated with a first advertisement is received from a first user. A quality score for the first advertisement is determined based at least in part on the received preference event. An advertisement fulfillment request is received. The request is responded to by selecting an advertisement based at least in part on the quality score of the first advertisement.

Abstract: Determining an item to present to a first user is disclosed. Preference information is received that comprises the preferences of a plurality of users associated with one or more items. User correlations are determined from the received preference information. For the first user, a set of other users most correlated with the first user is determined. One or more items are presented to the first user based at least in part on the preferences of the other users.

Abstract: Evaluating an item based on user reputation information is disclosed. Sharing event data is received. A graph is materialized from the received sharing event data. User reputation scores are determined based at least in part on the graph. A score is assigned to the item based at least in part on the user reputation scores of users associated with the item.