Method and system for targeted advertising based on topical memes

A system for performing meme-based targeted advertising, comprising:

• a computer, having a processor and a computer readable storage medium storing computer readable instructions for execution by the processor, wherein the instructions, when executed by the processor, cause the computer to perform a method comprising:
• analyzing web content against a defined topic;
• obtaining topic-matching content provided by one or more content sources, the topic-matching content being related to the defined topic;
• processing the topic-matching content;
• extracting topical memes associated with the topic-matching content, wherein each of the extracted topical memes is a point of discussion within the defined topic;
• measuring an engagement level for each piece of the topic-matching content;
• obtaining, based on the measuring, a respective viral dynamics metric for each said piece of the topic-matching content, wherein a viral dynamics metric indicates popularity of the piece of the topic-matching content;
• accumulating, for each of the extracted topical memes, the viral dynamics metrics of the pieces of the topic-matching content;
• obtaining, based on the accumulating, a respective aggregate viral dynamics value for each of the extracted topical memes;
• determining a most active meme from the extracted topical memes, based on the aggregate viral dynamics value for each of the extracted topical memes;
• associating the most active meme to subset content containing the most active meme, wherein the subset content is a subset of said topic-matching content;
• selecting advertising networks servicing said content sources;
• and
• delivering advertisements through the selected advertising networks to web pages containing the most active meme and included in the subset content.

A non-transitory computer readable medium, comprising computer code instructions stored thereon, which, when executed by a computer, perform a method comprising:

• analyzing web content against a defined topic;
• obtaining, based on the analyzing, topic-matching content related to the defined topic;
• processing the topic-matching content;
• extracting, based on the processing, topical memes associated with the topic-matching content, wherein each of the extracted topical memes is a point of discussion within the defined topic;
• measuring an engagement level for each piece of the topic-matching content
• obtaining, based on the measuring, a respective viral dynamics metric for each said piece of the topic-matching content, wherein a viral dynamics metric indicates popularity of the piece of the topic-matching content;
• accumulating, for each of the extracted topical memes, the viral dynamics metrics of the pieces of the topic-matching content;
• obtaining, based on the accumulating, a respective aggregate viral dynamics value for each of the extracted topical memes;
• determining a most active meme from the extracted topical memes, based on the aggregate viral dynamics value for each of the extracted topical memes;
• identifying web pages containing the most active meme;
• selecting an advertising network servicing a number of content sources hosting the identified web pages;
• selecting an advertisement assigned to the most active meme;
• and
• delivering said selected advertisement to said number of said content sources through said advertising network.