Modelling to identify influential bloggers in the blogosphere: A survey. (March 2017) - Khan, Hikmat Ullah; Daud, Ali; Ishfaq, Umer; Amjad, Tehmina; Aljohani, Naif; Abbasi, Rabeeh Ayyaz; Alowibdi, Jalal S.
Abstract: The user participatory nature of the social web has revolutionized the use of the conventional web. The social web is an integral part of our daily life. Due to the resulting exponential growth of the social web, a number of research domains have emerged, involving research activities that aim to study human nature, to analyse human sentiments and emotions, and to find the impact of various users in the social networks. Recently, the research focus has shifted to identifying a user's influence on other users in a social network. In the recent literature, we find a number of models proposed to find the most influential users in the blogging community. In this paper, we review the models to find these influential bloggers. The existing models are classified into feature-based and network-based categories. The feature-based models consider the salient factors to measure bloggers' influence. The network models, on the other hand, consider the graph-based social network structure of the bloggers to identify those who have the most impact on fellow members. This survey introduces each model with its features, novel aspects, and the datasets used. In addition to the discussion about the model, a comparative analysis of the datasets is presented. We conclude by discussing applications of the relevant literature, exploring open research issues and challenges, and sharing possible future directions in this active area of research. Highlights: Classification of finding influential bloggers models into feature-based and network-based. Chronological study of models. Comparison the real world blog datasets. Presented the potential applications of the research domain. Discussed current research challenges and future issues.