Abstract
Facebook is a world leader in social media, totaling 2.6 billion active monthly users in 2020. Their live streaming service, Facebook Live, is one of the fastest growing branches of the company, allowing creators to synchronously broadcast original content to the public. However, in the rapidly growing world of technology, Facebook Live faces fierce competition from other live streaming platforms (Twitch, YouTube Live, etc.) and well as other video on-demand providers (Netflix, Hulu, TikTok, etc.). Our team is working closely with Facebook Live to provide aid in navigating this competitive landscape and deliver a three to five-year strategic plan for the platform. The project will focus on Facebook Live’s growth opportunities from a multitude of perspectives, including, but not limited to interface modification, emerging markets, and competitive analysis. Facebook has been involved in a number of controversies in recent years, and it is important to consider the ethical concerns with a new product. With ~2 billion monthly users, Facebook has a huge impact on the world we live in. Many people consume news, engage in debate, and share their beliefs on the platform. Any new product that impacts those use cases can have far reaching consequences that extend beyond a website. An STS theory such as actor network theory lends itself very well to this problem since many of the factors that influence it are nonhuman. Facebook’s algorithms, bots, and laws all contribute to the current state of the platform. These factors are very important to consider when making further changes designed to remedy the problem of fake news. To analyze how Facebook can stop the proliferation of fake news I have analyzed historical data from Facebook transparency reports, as well as comparing different proposed solutions. Those solutions will include repealing Section 230, increased algorithmic recommendation, and a shift away from algorithmic recommendations. Through my research I have found that there is a consistent tradeoff between efficacy of these solutions and the disruption that they have; however, where that disruption is focused depends on the solution. Some solutions result in minimal disruption in how these platforms work but do not necessarily provide an adequate solution to the misinformation problem, while others would result in broad changes to the internet as a whole but could provide a meaningful solution. When considering the technical project along with my STS research it helps remind me that the solution is not an algorithm. While suggesting a recommender algorithm is easy and intuitive for a company such as Facebook, it is not necessarily the best solution and there may be an alternative that could make Facebook a less polarizing product.
