AgentSphere: A Novel Influencer Maximization Algorithm using Agent-Based Modeling in Social Networks
AgentSphere: A Novel Influencer Maximization Algorithm using Agent-Based Modeling in Social Networks |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-7 |
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| Year of Publication : 2024 | ||
| Author : Jyoti Sunil More, Vaishali V. Sarbhukan (Bodade), Yogesh Jadhav |
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| DOI : 10.14445/22315381/IJETT-V72I7P134 | ||
How to Cite?
Jyoti Sunil More, Vaishali V. Sarbhukan (Bodade), Yogesh Jadhav, "AgentSphere: A Novel Influencer Maximization Algorithm using Agent-Based Modeling in Social Networks," International Journal of Engineering Trends and Technology, vol. 72, no. 7, pp. 312-318, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I7P134
Abstract
Finding and using influencers to gain benefits is essential for marketing campaigns and information distribution in the field of social network analysis. In order to model and comprehend the intricate dynamics of social networks, this study presents AgentSphere, an inventive Influencer Maximisation Algorithm that makes use of Agent-Based Modeling (ABM). Each agent in the model represents a real-world user, capturing their various traits, actions, and capacities for impact. AgentSphere provides a realistic and nuanced depiction of social relationships through dynamic interactions and information dispersion, which helps with influencer optimisation and correct identification. The creation, application, and assessment of AgentSphere are presented in this research study, demonstrating its efficacy above conventional methods. The outcomes show how flexible AgentSphere is to the ever-changing social network landscape, making it an invaluable resource for influencer maximization in various domains.
Keywords
Agent based modeling, Social networks, Social media, Influencer maximization.
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