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Examining the role of social media likes in follower network evolution

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Credit: Pixabay/CC0 Public Domain

In a recent study centered on China’s primary social shopping community, researchers shed light on the factors influencing the growth of the follower networks of content creators. The empirical study, published in the International Journal of Computational Science and Engineering, focuses on the role of social media likes in this process, revealing intriguing insights pertinent to the content creators themselves and to marketing executives hoping to benefit from the network reach of those creators.

Tao Wang of Putian University in Putian, Shuang Fu of Xiamen University Tan Kah Kee College in Zhangzhou, and Zhiyi Wu of Shanghai University of Finance and Economics in Shanghai, China, have established that the number of likes a content creator receives is crucial to the expansion of their follower base.

However, they also discerned a rather nuanced observation: prior follower count can moderate this relationship such that, paradoxically, a higher previous follower count can negatively affect the growth of the follower network. The team suggests that this indicates a rather complex interplay between approval and perceived audience size.

The work thus has implications for industry practitioners and will also be of interest to others studying e-commerce and social media content creators and influencers. In practical terms, the research suggests that content creators should prioritize increasing the number of likes they receive from users, as this directly contributes to the expansion of their follower network and ultimately their influence.

Community administrators can address the moderating effect of previous follower count by broadening content distribution to counteract any detrimental effect. Conversely, marketers and community members gain strategic insights for collaboration and follower selection. Future work might investigate other areas beyond the online social shopping community in China, potentially searching for more general conclusions about influence and reach.

In essence, the research could help us unravel some of the complex dynamics at play in online social shopping communities. It underscores the role of social media likes in how much reach a given content creator might achieve as well as considering the blunt tool of popularity. Likes, once perceived merely as tokens of approval, now emerge as elements that can shape how successful a content creator might be.

More information:
Tao Wang et al, Examining the role of likes in follower network evolution based on a dynamic panel data model, International Journal of Computational Science and Engineering (2023). DOI: 10.1504/IJCSE.2023.135296

Citation:
Examining the role of social media likes in follower network evolution (2023, December 14)
retrieved 14 December 2023
from https://phys.org/news/2023-12-role-social-media-network-evolution.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.




social media likes
Credit: Pixabay/CC0 Public Domain

In a recent study centered on China’s primary social shopping community, researchers shed light on the factors influencing the growth of the follower networks of content creators. The empirical study, published in the International Journal of Computational Science and Engineering, focuses on the role of social media likes in this process, revealing intriguing insights pertinent to the content creators themselves and to marketing executives hoping to benefit from the network reach of those creators.

Tao Wang of Putian University in Putian, Shuang Fu of Xiamen University Tan Kah Kee College in Zhangzhou, and Zhiyi Wu of Shanghai University of Finance and Economics in Shanghai, China, have established that the number of likes a content creator receives is crucial to the expansion of their follower base.

However, they also discerned a rather nuanced observation: prior follower count can moderate this relationship such that, paradoxically, a higher previous follower count can negatively affect the growth of the follower network. The team suggests that this indicates a rather complex interplay between approval and perceived audience size.

The work thus has implications for industry practitioners and will also be of interest to others studying e-commerce and social media content creators and influencers. In practical terms, the research suggests that content creators should prioritize increasing the number of likes they receive from users, as this directly contributes to the expansion of their follower network and ultimately their influence.

Community administrators can address the moderating effect of previous follower count by broadening content distribution to counteract any detrimental effect. Conversely, marketers and community members gain strategic insights for collaboration and follower selection. Future work might investigate other areas beyond the online social shopping community in China, potentially searching for more general conclusions about influence and reach.

In essence, the research could help us unravel some of the complex dynamics at play in online social shopping communities. It underscores the role of social media likes in how much reach a given content creator might achieve as well as considering the blunt tool of popularity. Likes, once perceived merely as tokens of approval, now emerge as elements that can shape how successful a content creator might be.

More information:
Tao Wang et al, Examining the role of likes in follower network evolution based on a dynamic panel data model, International Journal of Computational Science and Engineering (2023). DOI: 10.1504/IJCSE.2023.135296

Citation:
Examining the role of social media likes in follower network evolution (2023, December 14)
retrieved 14 December 2023
from https://phys.org/news/2023-12-role-social-media-network-evolution.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.

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