Abstract
Interest in Opinion Mining has been growing steadily in the last years, mainly because of its great number of applications and the scientific challenge it poses. Accordingly, the resources and techniques to help tackle the problem are many, and most of the latest work fuses them at some stage of the process. However, this combination is usually executed without following any defined guidelines and overlooking the possibility of replicating and improving it, hence the need for a deeper understanding of the fusion process becomes apparent. Information Fusion is the field charged with researching efficient methods for transforming information from different sources into a single coherent representation, and therefore can be used to guide fusion processes in Opinion Mining. In this paper we present a survey on Information Fusion applied to Opinion Mining. We first define Opinion Mining and describe its most fundamental aspects, later explain Information Fusion and finally review several Opinion Mining studies that rely at some point on the fusion of information