Classification of deceptive opinions using a low dimensionality representation

Abstract

Opinions in social media play such an important role for customers and companies that there is a growing tendency to post fake reviews in order to change purchase decisions and opinions. In this paper we propose the use of different features for a low dimension representation of opinions. We evaluate our proposal incorporating the features to a Support Vector Machines classifier and we use an available corpus with reviews of hotels in Chicago. We perform comparisons with previous works and we conclude that using our proposed features it is possible to obtain competitive results with a small amount of features for representing the data. Finally, we also investigate if the use of emotions can help to discriminate between truthful and deceptive opinions as previous works show to happen for deception detection in text in general.