http://www.usatoday.com/money/advertising/2005-06-22-viral-usat_x.htm

This article talks about a popular way of advertising called viral marketing. This technique has become increasingly more popular in recent years. Viral marketing is a way of advertising that uses already existing social networks to increase brand awareness. It is spread in a viral process, similar to pathological and computer viruses, usually by some form of communication . It could be spread by word of mouth, the Internet, text messages, and so forth. With the advent of the internet, viral marketing has been able to spread across social networks very quickly. Viral marketing relies on the consumers to pass on the advertisements to friends, so it is important that companies make their ads catchy and creative so that others will pass it along.

Most recently, movies such as Batman Returns and Cloverfield have taken advantage of viral marketing. Their trailers flooded the internet, and has been spreading to more users very rapidly. One good example of viral marketing is Hotmail. Hotmail only spent $50,000 on traditional advertising and they were able to gain 18 million users in 12 months. Hotmail’s early success can be attributed to users telling their family and friends about their service. They also used viral advertising by having advertisements embedded into each email.

http://www-personal.umich.edu/~ladamic/papers/viral/viral-market-short.pdf

This article goes into more detail about how viral advertising based on recommendations relates to information cascades. Here in this model, one person makes the decision whether or not to buy an object. Subsequent buyers can read the recommendations of previous buyers on whether or not to buy the object. Here we see how people’s decisions to buy a product will be affected by what other’s say about the product. This recommendation system is a slightly different information cascade since only those that have recommended the product have purchased it. Sites like Amazon offer interesting statistics like how many people that viewed the product actually purchased it. So we know the decisions of what other people made, but there is no clear signal like in the model presented in class, where people received a signal of High or Low. The paper also notes that as a person gets more and more recommendations for a product, the probability of purchasing that product increases; however, there is a saturation point, where subsequent recommendations beyond the saturation point have no longer increases the chance of purchasing. This shows how there are many variables in recommendations that can affect the probability of purchasing something.