Targeted Advertising and Strong Triadic Closure
This article describes targeted advertising, how it works, and what potential responses to it are. However, while it describes the mechanism in which Internet Service Providers and websites such as Amazon, eBay, and any other retail site can learn what you might be interested in, it does not go into depth on how algorithms determine which products are most likely to be bought by each consumer. In reality, this practice is deeply influenced by the concept of Strong Triadic Closure. The Strong Triadic Closure Property means that if one node A has strong connections with both node B and node C, then nodes B and C will have either a strong or weak connection between them. While Strong Triadic Closure does not necessarily hold true for all networks, it provides a starting point for advertisers to show products to potential consumers. If a strong connection is formed between a product that is directly related to another product or a product and a person that has recently purchased it, and a weak connection is formed between a product that a person is interested in buying, by assuming Strong Triadic Closure, advertisers can introduce related products to a consumer algorithmically.
This then takes steps towards fulfilling the property, as often times a consumer will become interested in a product they see in an ad, creating a weak tie between the newly introduced product and the consumer. Additionally, the more products companies can sell with targeted advertising, the more products they can attempt to create ties with the consumer, therefore creating a more interconnected advertising network and once again selling more products to consumers. As the article states, this property of targeted advertising then provides more powerful information to advertisers, which then creates a more effective advertising network and repeats the cycle over and over again. The principle of Strong Triadic Closure shows how the theory behind targeted advertising creates more sales reliably at the network level.