Topic-based influential user detection: a survey

Abstract Online Social networks have become an easy means of communication for users to share their opinion on various topics, including breaking news, public events, and products. The content posted by a user can influence or affect other users, the who could high number are called influential users. Identifying such has wide range applications in field marketing, product advertisement, recommendation, brand evaluation. However, users’ varies different hence tremendous interest been shown towards identifying topic-based over past few years. Topic-level information be used stages detection (IUD) problem, data gathering, construction network, quantifying between two analyzing impact detected user. This opened up opportunities utilize existing techniques model analyze topic-level online social networks. In this paper, we perform comprehensive study infer We present detailed review these approaches taxonomy while highlighting challenges limitations associated with each technique. Moreover, evaluation literature overcome that arise evaluating IUD approaches. Furthermore, closely related research topics open questions discussed provide deep understanding future directions.