Using Deep Learning Predictors and Latent Dirichlet Allocation to Identify Key Issues Affecting Clients in Chilean Restaurants

Abstract

In this work, we use a general sentiment analysis methodology to train different Deep Learning predictors so that a proper quantitative valuation can be obtained based on qualitative information given by customers on social media (comments). We use Convolutional Neural Network and Long Short-Term Memory combined with different inputs including the body of the comments and its title. With the trained predictors we classify a large set of comments regarding negative positive customer experiences. Finally we use Latent Dirichlet Allocation algorithm to identify the specific issues appearing on the comments related to negative customer experience ratings.