UGC (User Generated Content) Sites and Network Effects
We’ve been discussing social network effects in class. Network effects matter a lot to many companies in tech industry, especially to those UGC (User Generated Content) sites, where users are contributors to the site contents. The young company TripAdvisor is a typical example. According to the Forbes article, How TripAdvisor Grows Scale and Network Effects: Expertise in Gathering UGC, “TripAdvisor builds scale and creates network effects from User Generated Content (UGC) on the most atomic level — by contributor and user.” The article summarizes, from an interview with Adam Medros, TripAdvisor’s VP of Global Product, that the keys of attracting traffic are “Community”, “Platform Ubiquity”, “Context”, and “Community Status”. I’ll mainly talk about “Community” and “Context”.
“Community” is most related to what’s discussed in lecture. According to the article, Medros says, “If you asked our users why they write reviews they say ‘TripAdvisor helped me and I want to help others.’” Users “copy” other users’ actions and behaviors. Users see other people giving advice to the community on TripAdvisor. They’re not exactly sure why people choose to do that, but many users still follow them. It’s possible that the users think people who comment know some information that they don’t, and it’s also possible that there’s direct benefit – people feel good about being altruistic and helpful. It’s simply about happiness.
“Context” is a very interesting factor. It’s also about social network effects, but more about in which situations effects are stronger than in others. The article talks about the idea of “looking for people like me”. If the users are able to tell that the reviewer has something in common with them, they tend to trust his or her comments more. This idea probably could be generalized. We see two groups of people making different decisions without knowing what they are truly thinking about. People in group A are more related to us – lots of them are friends or Facebook friends with us, for example, while people in group B are less like us. Which crowd would we follow? Most likely group A. The reason might be information based. Both group might know something that we don’t, but it’s more possible that the information known to group A is more useful to us, than that known to group B, since we’re more like people in group A. For similar reasons, considering direct benefits, if they are somewhat conditional, we’re more possible to enjoy them as people in group A, if we make same decision as them.
Source: http://www.forbes.com/sites/avaseave/2013/06/20/how-tripadvisor-grows-scale-and-network-effects-expertise-in-gathering-ugc/