Following the Crowd: Understanding social cascades in the 21st century
This article brings up a few main points we covered in networks, specifically in the information cascades chapter. One of the benefits of living in a technologically advanced era is having access to a vast amount of information right at our fingertips. Not sure which hotel to stay at during your vacation? Trip advisor will let you know which ones are popular and in high demand. Not familiar with the restaurants around NYC? Yelp will have all the reviews and photos of the food, along with ratings that show the number of people who stop by.
This article mentions how social proof is an effective way to prove to potential buyers that the service or product is reputable based on the number of positive reviews other people left behind. “People are wired to learn from the actions of others, and this can be a huge driver of consumer behavior.” According to a study in the article, saying that “almost 75% of other guests help by using their towels more than once” or adding the words “of other guests that stayed in this room” had more influence on people reusing towels in hotel rooms. Another concept described in the article was the “wisdom of the crowd” social proof. Telling consumers that the popularity or large numbers of users implies “a million people can’t be wrong.” Following the crowd in this case would be beneficial for them because the vast majority did not have a negative experience.
This ties into what we learned about during lecture, particularly the informational effects and direct-benefit effects. People want to copy the behavior of others if there is a direct benefit to them from aligning their behavior with the rest of the population. For instance, if very few people are using MySpace, it makes the site useless and less valuable. Evaluating whether to use it or not would depend on the number of people who own a MySpace account as well. In this case, people would benefit if the social media has a larger user population like Facebook, Snapchat and Instagram.
In networks, we also discussed the simple herding experiment, which states that decisions are made sequentially and can be observed by others. Each person has some private information that helps guide their decision and can make inferences about this private information from what they do. Bayes Rule gives us the mathematical model for this type of information cascade and shows us that cascades can be fragile. For example, even if a popular opinion about a product has persisted for a long time, one bad review can possibly be overturned with little effort. These concepts demonstrate how the behavior of others can shape our opinions and those after us.
Article: https://techcrunch.com/2011/11/27/social-proof-why-people-like-to-follow-the-crowd/