Affective Computing Databases: In-Depth Analysis of Systematic Reviews and Surveys

Abstract

The field of affective computing (AffC) is a hot research topic, where keeping track of the latest state-of-the-art can be cumbersome. Probably, due to this, a huge increase in publications of systematic reviews or surveys (SRoS) is appearing in different journals, covering various aspects such as databases, methods, and overall perspectives. Nevertheless, this increase does not mean more and better information, or at least a clarification of information. The present study analyses 10 SRoS, all published within the last 4 years, focusing only on covering AffC databases, with emphasis on collections where emotion or sentiment can be extracted from the body. It was observed that, depending on the SRoS, different information was presented, sometimes with missing or discrepant data, due to lack of information or by the way it was interpreted. As a result, from those 10 SRoS, a total of 111 different databases were analyzed, which were segmented into three groups (tiers, i.e., citation-based categorization) by their relative importance of appearance in the SRoS. In addition, it is proposed a taxonomy with a minimum set of characterizing information that researchers should address when publishing or reviewing databases.