Finding influential users in microblogs: state-of-the-art methods and open research challenges

Umar Ishfaq, Hikmat Ullah Khan, Shahid Iqbal and Mohammed Alghobiri

Behaviour and Information Technology, 2022, vol. 41, issue 10, 2215-2258

Abstract: Social networks are online platforms that people use for interaction, information sharing and propagation of new ideas. Finding influential users in online social networks is a significant research problem due to its vast research applications in information diffusion, marketing and advertising. The relevant literature presents several models proposed for identifying influential users in social networks. In this survey, we present a review of the most relevant studies on influential users mining in microblog networks. First, we propose a new taxonomy by classifying the influence finding algorithms into five main categories based on their underlying framework and baseline methods. Second, each study is analysed according to the proposed framework, experimental datasets, validation approaches and evaluation results. Finally, the survey concludes with discussion on applications from the relevant literature, exploring open research challenges and presenting possible future research directions. The findings of this survey indicate that influential users mining in microblogs has many applications in marketing, advertising and information diffusion. In addition, this survey can be used as a guideline, particularly by young researchers, for establishing a baseline before initiating a research or identifying attractive as well as relevant research insights.

Date: 2022
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DOI: 10.1080/0144929X.2021.1915384

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