Rating Movies & Information Cascades
In a world full of algorithm recommendations on Google, Youtube, and Tiktok, sometimes we look for ratings from others for that personal touch. Or sometimes, they fall into our lap. Whether you overhear a stranger’s conversation or ask your friend about their weekend, it seems like there is always another movie to add to that list on your notes app. In “Do I Follow My Friends or the Crowd? Information Cascades in Online Movie Ratings” Young-Jin Lee, Kartik Hosanagar, and Yong Tan discuss the role of friendships in movie reviews.
More specifically, they explore how ratings are generated and how they are affected by prior ratings of strangers versus friends. For strangers, they found that individuals had a low chance of following through with positively rated movies. On the other hand, when a friend rated a movie, that rating always induced an information cascade among a friend group to watch that movie. We can define an information cascade as making a decision based on the decisions of other people, regardless of their own information.
This conclusion is not fully surprising, considering that individuals will weigh the ratings of people they care about more than strangers. If only to have a shared experience or to fit in with other friends. But the fact that this always occurs is surprising. It speaks to the power we put on our friends. And it provokes another question: How much do our friends affect our knowledge of the world? It is described that friends’ ratings can create information cascades and affect the movies we consume without reliability. But what happens when that media is not only about whether the last Marvel movie was good or bad? What happens when that media is the news articles we read and the books we use to educate ourselves? Such ratings and information cascades from friends and friend groups can profoundly affect our understanding of the world for better and for the worse. As the article suggests, in order to more accurately understand the world we live in, we need to “question … the reliability of ratings as unbiased indicators of quality and advocate the need for techniques to debias rating systems.”
https://repository.upenn.edu/cgi/viewcontent.cgi?article=1324&context=marketing_papers