Title: Who influences the influencer - a network analytical study of an influencer's peer-based importance

Authors: Jens K. Perret

Addresses: International School of Management, Im MediaPark 5c, 50670 Cologne, Germany

Abstract: In contrast to studies focusing on determinants of influencers' relevance which are limited to mostly qualitative discussions, this study focuses on the similarity between social media influencers as relevant figures of a network and the mathematical study of social networks, i.e., the use of network statistics and centrality measures. A dataset of 255 influencers spanning a period of four years from the field of women's fashion present on the social media platform Instagram has been used to empirically determine a model of an influencer's relative importance in the network of its peers. By using regression analysis (panel and cross-sectional) as well artificial neural networks, the importance of the four main factors: followers, reach, engagement rate and posting frequency can consistently be established as well as their causal effects and the path dependency of an influencer's importance across years.

Keywords: social media; Instagram; influencer; eigenvector centrality; network; social network analysis; women's fashion; panel data; regression; artificial neural networks; fashion.

DOI: 10.1504/IJEMR.2024.138301

International Journal of Electronic Marketing and Retailing, 2024 Vol.15 No.3, pp.370 - 392

Received: 31 Oct 2021
Accepted: 18 Feb 2022
Published online: 01 May 2024 *

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