Universiti Teknologi Malaysia Institutional Repository

A method to detect influencers in social networks based on the combination of amplification factors and content creation

Huynh, Tai and Nguyen, Hien D. and Zelinka, Ivan and Pham, Xuan Hau and Pham, Vuong T. and Selamat, Ali and Krejcar, Ondrej (2022) A method to detect influencers in social networks based on the combination of amplification factors and content creation. PLoS ONE, 17 (10). pp. 1-31. ISSN 1932-6203

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Official URL: http://dx.doi.org/10.1371/journal.pone.0274596

Abstract

A social network is one of the efficient tools for information propagation. The content is the bridge between the product and its customers. Evaluating the user’s content creation is a valuable feature to improve information spreading on the social network. This paper proposes a method for extracting brand value with influencers by combining the user’s amplification and content creation in influencer marketing. The amplification factors are studied based on the propagation of the posts on the social network in a duration time. Those factors are more valuable than before when using influencer marketing at a determined time. Moreover, the content creation score is also studied to measure content creation based on the passion point with a brand and its quality. The amplification factors and content creation score are combined to analyze posts’ interest in detecting the emerging influent users for a product in the influencer marketing campaign. Using the amplification factors, the passion points, and the content creation score, a system to manage the influencer marketing on Facebook has been constructed and tested in the real-world campaign. The experimental results show that the proposed method’s influencers bring the conversion rate’s efficiency and revenue in the influencer marketing campaign.

Item Type:Article
Uncontrolled Keywords:social media, social network, methodology
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions:Computing
ID Code:103658
Deposited By: Yanti Mohd Shah
Deposited On:22 Nov 2023 00:22
Last Modified:22 Nov 2023 00:22

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