A computer algorithm, affectionately referred to as the “bestseller-ometer,” examines a huge amount of literature for qualities that make bestselling fiction. According to The Atlantic, the algorithm is capable of identifying a bestseller upwards of 80 percent of the time. This success rate is achieved by going off a list of novels from the past 30 years and identifying New York Times best sellers. This is one of the ways in which data-driven initiatives are attempting to better understand the way that the human brain identifies concepts, and it could change the way that publishers identify potential best sellers. Like most good ideas, this concept was borne from a question that needed to be...
