Prediction of User-Brand Associations Based on Sentiment Analysis

Abstract

Finding the right users to be chosen as targets for advertising campaigns is not a trivial task, and it may allow important commercial advantages. A novel approach is presented here for the recommendation of new possible consumers to brands interested in distributing advertising campaigns, ranked according to the “compatibility” between users and brands. A database containing both descriptions associated with different brands, and textual information about users' opinions on different topics, is required in input. Then, sentiment analysis techniques are applied to measure to what extent the users match with the brands, based on the texts associated with their opinions. The approach has been tested on both synthetic and real datasets, and with two different formulations, showing promising results in all the considered experiments.