Imitating The Decisions Of Others
[P]eople influence each other’s behavior. In short, as you see more and more people doing something, you generally become more likely to do it as well. Understanding why this happens, and what its consequences are, is a central issue for our understanding of networks and aggregate behavior.
At a surface level, one could hypothesize that people imitate the decisions of others simply because of an underlying human tendency to conform: we have a fundamental inclination to behave as we see others behaving. This is clearly an important observation, but as an explanation it leaves some crucial questions unresolved. In particular, by taking imitation as a given, we miss the opportunity to ask why people are influenced by the behavior of others. This is a broad and difficult question, but in fact it is possible to identify multiple reasons why even purely rational agents — individuals with no a priori desire to conform to what others are doing — will nonetheless copy the behavior of others.
One class of reasons is based on the fact that the behavior of others conveys information. You may have some private information on which to base a decision between alternatives, but if you see many people making a particular choice, it is natural to assume that they too have their own information, and to try inferring how people are evaluating different choices from how they are behaving. In the case of a Web site like YouTube or Flickr, seeing a lot of people using it can suggest that these people know something about its quality. Similarly, seeing that a certain restaurant is extremely crowded every weekend can suggest that many people think highly of it. But this sort of reasoning raises surprisingly subtle issues: as many people make decisions sequentially over time, the later decisions can be based in complex ways on a mixture of private information and inferences from what has already happened, so that the actions of a large set of people can in fact be based on surprisingly little genuine information. In an extreme form of this phenomenon we may get information cascades, where even rational individuals can choose to abandon their private information and follow a crowd.
There is a completely different but equally important class of reasons why people might imitate the behavior of others — when there is a direct benefit from aligning your behavior with that of others, regardless of whether they are making the best decision. Let’s go back to our examples of social-networking and media-sharing sites. If the value of such sites is in the potential to interact with others, to have access to a wide range of content, and to have a large audience for the content you post, then these types of sites become more and more valuable as people join them. In other words, regardless of whether YouTube had better features than its competitors, once it became the most popular video-sharing site, there was almost by definition an added value in using it. Such network effects amplify the success of products and technologies that are already doing well; in a market where network effects are at work, the leader can be hard to displace. Still, this type of dominance is not necessarily permanent; as we will see, it is possible for a new technology to displace an old one if it offers something markedly different — and often when it starts in a part of the network where there is room for it to take hold.
These considerations show how popularity — as a general phenomenon — is governed by a “rich-get-richer” feedback process in which popularity tends to build on itself. It is possible to build mathematical models for this process, with predictions for the distribution of popularity that are borne out by empirical data — a picture in which society’s attention is divided between a small number of prominent items and a “long tail” of more obscure ones.
Quoted on Sat Feb 16th, 2013