Recently I’ve been looking at recommender systems , which is one of the most prevalent application of machine learning in the industry. A recommender system looks at your previous consumption behaviors (e.g. movies you watched, articles you read, products you purchased, etc) and suggests items that are (hopefully) relevant to your interests. You actually interact with recommender systems every day when using services like YouTube, Amazon, and Netflix; they often come with statements saying “you may also like…” or “recommended for you…”. Other online news aggregators/publishers also have similar feature under new articles although I’m not sure if their recommendations are automatically generated or hand-picked by their staffs/editors (o_o)). One interesting observation from a dataset I’m experimenting with is that ’emotions’ seems to play an important role in shaping people’s opinion toward a movie. Other factors, including the overhyped social influence, are not as indicative of user reception as the emotions or feelings evoked by the movie. My retrospective thoughts and observations agree with this finding. Unless we can build captivating products that arouse and inspire its users, like some of the Apple tech devices or the wide range of free Google services, they will soon be forgotten..