Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

Tai Huynh, Hien Nguyen, Ivan Zelinka, Dac Dinh and Xuan Hau Pham
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Tai Huynh: Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
Hien Nguyen: Faculty of Computer Science, University of Information Technology, Ho Chi Minh City 700000, Vietnam
Ivan Zelinka: Department of Computer Sciences, FEI VBS Technical University of Ostrava Tr. 17. Listopadu 15, Ostrava 70800, Czech Republic
Dac Dinh: Kyanon Digital, Ho Chi Minh City 700000, Vietnam
Xuan Hau Pham: Faculty of Engineering – Information Technology, Quang Binh University, Dong Hoi City 510000, Quang Binh, Vietnam

Sustainability, 2020, vol. 12, issue 7, 1-16

Abstract: Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.

Keywords: influencer; opinion leaders; social pulse; information propagation; passion point; centrality measure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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