System and method for content based social recommendations and monetization thereof

A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a processor of a computing device, perform a method comprising:

• identifying an image collection associated with a first user within a photo-sharing network;
• parsing each image in the image collection to identify content of each image;
• determining a first content category based on the content of each image;
• grouping each image associated with the first content category into a first image cluster;
• analyzing each image of the first cluster to determine an occurrence of a digital representation of a second user within the first cluster;
• providing a recommendation to the first user and the second user, said recommendation facilitating a social relationship between the first user and the second user within the photo-sharing network;
• and
• serving an advertisement to the first user and the second user in accordance with the recommendation and based on the first content category.

A system comprising:

• at least one computing device comprising:
• memory storing computer-executable instructions;
• and
• one or more processors for executing said computer-executable instructions, comprising:
• identifying an image collection associated with a first user within a photo-sharing network;
• parsing each image in the image collection to identify content of each image;
• determining a first content category based on the content of each image;
• grouping each image associated with the first content category into a first image cluster;
• analyzing each image of the first cluster to determine an occurrence of a digital representation of a second user within the first cluster;
• providing a recommendation to the first user and the second user, said recommendation facilitating a social relationship between the first user and the second user within the photo-sharing network;
• and
• serving an advertisement to the first user and the second user in accordance with the recommendation and based on the first content category.