  The social media revolution has changed the way that brands interact with
consumers. Instead of spending their advertising budget on interstate
billboards, more and more companies are choosing to partner with so-called
Internet "influencers" --- individuals who have gained a loyal following on
online platforms for the high quality of the content they post. Unfortunately,
it's not always easy for small brands to find the right influencer: someone who
aligns with their corporate image and has not yet grown in popularity to the
point of unaffordability. In this paper we sought to develop a system for
brand-influencer matchmaking, harnessing the power and flexibility of modern
machine learning techniques. The result is an algorithm that can predict the
most fruitful brand-influencer partnerships based on the similarity of the
content they post.
