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Paper Number
2217
Paper Type
Complete
Description
As collaborations between brands and influencers become increasingly popular, predicting the capacity of an influencer to generate engagement has garnered increasing attention from researchers. Traditionally, managers have been relying on follower-based statistics to identify individuals with potential to reach a vast number of users on social-media. However, this approach may often direct managers to accounts with millions of followers accompanied with high recruiting costs. In this paper, we argue that the network structure of influencers is a useful measure for capturing an influencer’s ability to generate engagement. Using Instagram data, we perform a deep-learning analysis on the social network of influencers and show that the network structure explains a large share of the variations in user engagement, even outperforming traditionally used variables such as the number of followers in the case of comments. This study contributes to the emergent literature on the importance of social ties in the digital environment
Recommended Citation
Malhotra, Pankhuri; Daviet, Remi; and Kim, Seungbae, "Importance of Social Network Structures in Influencer Marketing" (2022). ICIS 2022 Proceedings. 12.
https://aisel.aisnet.org/icis2022/social/social/12
Importance of Social Network Structures in Influencer Marketing
As collaborations between brands and influencers become increasingly popular, predicting the capacity of an influencer to generate engagement has garnered increasing attention from researchers. Traditionally, managers have been relying on follower-based statistics to identify individuals with potential to reach a vast number of users on social-media. However, this approach may often direct managers to accounts with millions of followers accompanied with high recruiting costs. In this paper, we argue that the network structure of influencers is a useful measure for capturing an influencer’s ability to generate engagement. Using Instagram data, we perform a deep-learning analysis on the social network of influencers and show that the network structure explains a large share of the variations in user engagement, even outperforming traditionally used variables such as the number of followers in the case of comments. This study contributes to the emergent literature on the importance of social ties in the digital environment
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15-SocialMedia