Social media platforms represent an essential tool for both consumers and marketers. Meanwhile,
luxury fashion brands play a key role in fashion, one of the most important industries of the
world economy. Despite assumptions to the contrary, social media platforms and luxury fashion
brands do mix, especially in the recent time. Consequently, it is worth asking whether it is
possible to predict the reaction a post will generate in the audience of luxury fashion brands.
This new question is the one this thesis intends to answer. To do so, the concept of reaction is
defined through a novel composite index that is created and named Tweet reaction overall score
(TROS), which is one of the solid and relevant contributions this thesis makes. Then, several
predictive models are implemented, based on a wide range of different learning algorithms. The
results show that it is indeed possible to predict the TROS that a post on Twitter will obtain in
the audience of luxury fashion brands the day it is posted
