Quality Assessment of Social Media: Lessons Learnt from the Literature

Abstract

Social networks are a subject of great interest worldwide. Year after year we have experienced an increase in the number of new users and, even, the creation of new technologies (i.e. augmented reality, 360º cameras, …) and new social networks. However, this phenomenon is contrasted with the appearance of automatic programs (bots) and fake news that can affect the quality of published information. This paper presents the state of the art of the quality of the information found in different social networks. In addition, we propose a series of learnt lessons to be followed in order to develop a theoretical application that measures the quality of a user generated information for a given event.