Systematic literature review on identifying influencers in social networks

Abstract

Considering the ever-increasing size and complexity of social networks, developing methods to extract meaningful knowledge and information from users’ vast amounts of data is crucial. Identifying influencers on social networks is one of the essential investigations on these networks and has many applications in marketing, advertising, sociology, behavior analysis, and security issues. In recent years, many studies have been conducted on analyzing and identifying influencers on social networks. Therefore, in this article, a Systematic Literature Review (SLR) has been performed on previous studies about the methods of identifying influencers. To this end, we review the definitions of influencers, the datasets used for evaluation purposes, the methods of identifying influencers, and the evaluation techniques. Furthermore, the quality assessment of the recently published papers also has been performed in different aspects to find whether research about identifying influencers has progressed. Finally, trends and opportunities for future studies about influencers’ identification are presented. The result of this SLR shows that the quantity and quality of articles in the field of identifying influencers in social networks are growing and progressive, which shows this field is a dynamic and active area of research.