Introduction

Big data and mining social media trends has done great things for recommendation engines for all sorts of media types, but several of the inherent design features of these systems has lead to flaws in the system. I propose a solution that circumvents many of the issues of a music recommendation system by focusing on ‘little data’. That is: users whose influence is more significant than an average user, whom I call “Tastemakers”. The core concept is to design a service that feels more like a staff wall at a local record store than any “web service”.