17. One or more non-transitory computer readable media having instructions stored thereon, which when executed by a set of one or more processors causes the set of one or more processors to perform operations comprising: generating, in response to a first input provided by a user source, a recommendation container configured to receive content recommendations from at least one recommender source that is a subset of social-network entities linked to the user source, wherein the recommendation container is user definable by only the user source; assigning a user-defined topic to the recommendation container, wherein the user-defined topic is defined by a second input from the user source; associating, in response to a third input from the user source, the at least one recommender source with the recommendation container; assigning a trust rating, in response to a fourth input from the user source, to the at least one recommender source specifically for the user-defined topic, wherein the trust rating-represents a degree of trust that the user source has in the at least one recommender source, as a recommendation source, to provide content recommendations of value specifically for the user-defined topic; detecting a set of content recommendations provided by the at least one recommender source, wherein the set of content recommendations are on a plurality of topics, and wherein at least one of the plurality of topics includes the user-defined topic; filtering the set of content recommendations using the user-defined topic forming a subset of content recommendations that are classified by the user-defined topic; determining individual recommendation ratings for each content recommendation in the subset of content recommendations, wherein the individual recommendation ratings are set by the at least one recommender source and represent individual degrees of preference that the at least one recommender source has for each content recommendation in the subset of content recommendations; calculating individual ranking scores for each content recommendation in the subset of content recommendations by computing each individual recommendation rating with the trust rating; and ranking the subset of content recommendations into a ranked list based on the individual ranking scores for each content recommendation in the subset of content recommendations.
17. One or more non-transitory computer readable media having instructions stored thereon, which when executed by a set of one or more processors causes the set of one or more processors to perform operations comprising: generating, in response to a first input provided by a user source, a recommendation container configured to receive content recommendations from at least one recommender source that is a subset of social-network entities linked to the user source, wherein the recommendation container is user definable by only the user source; assigning a user-defined topic to the recommendation container, wherein the user-defined topic is defined by a second input from the user source; associating, in response to a third input from the user source, the at least one recommender source with the recommendation container; assigning a trust rating, in response to a fourth input from the user source, to the at least one recommender source specifically for the user-defined topic, wherein the trust rating-represents a degree of trust that the user source has in the at least one recommender source, as a recommendation source, to provide content recommendations of value specifically for the user-defined topic; detecting a set of content recommendations provided by the at least one recommender source, wherein the set of content recommendations are on a plurality of topics, and wherein at least one of the plurality of topics includes the user-defined topic; filtering the set of content recommendations using the user-defined topic forming a subset of content recommendations that are classified by the user-defined topic; determining individual recommendation ratings for each content recommendation in the subset of content recommendations, wherein the individual recommendation ratings are set by the at least one recommender source and represent individual degrees of preference that the at least one recommender source has for each content recommendation in the subset of content recommendations; calculating individual ranking scores for each content recommendation in the subset of content recommendations by computing each individual recommendation rating with the trust rating; and ranking the subset of content recommendations into a ranked list based on the individual ranking scores for each content recommendation in the subset of content recommendations. 20. The one or more non-transitory computer readable media of claim 17 , further comprising: providing an instance of the recommendation container to at least one additional user source; receiving at least one additional trust rating from the at least one additional user source, wherein the at least one additional trust rating represents a degree of trust that the at least one additional user source has in the recommendation container, as an additional recommendation source, specifically for the user-defined topic; and ranking the subset of content recommendations into at least one additional ranked list by computing the individual ranking scores with the at least one additional trust rating.