  In this paper, we examine the use case of general adversarial networks (GANs)
in the field of marketing. In particular, we analyze how GAN models can
replicate text patterns from successful product listings on Airbnb, a
peer-to-peer online market for short-term apartment rentals. To do so, we
define the Diehl-Martinez-Kamalu (DMK) loss function as a new class of
functions that forces the model's generated output to include a set of
user-defined keywords. This allows the general adversarial network to recommend
a way of rewording the phrasing of a listing description to increase the
likelihood that it is booked. Although we tailor our analysis to Airbnb data,
we believe this framework establishes a more general model for how generative
algorithms can be used to produce text samples for the purposes of marketing.
