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Using attractiveness model for actors ranking in social media networks
Ziyaad Qasem1, Marc Jansen1, Tobias Hecking2
1Computer Science Institute, University of Applied Science Ruhr West, Lützowstraße 5, 46236 Bottrop, Germany.
Computational Social Networks
|December 22, 2017
Summary
This study introduces a new measure for identifying influential actors on social media by analyzing their ability to attract other key individuals. This approach aids in understanding community dynamics and optimizing information diffusion strategies.
Area of Science:
- Social Network Analysis
- Information Science
Background:
- Identifying influential actors on social media platforms like Twitter and Facebook is crucial for opinion gathering, marketing, and trend prediction.
- Understanding influence dynamics is key to managing online communities and information flow.
Purpose of the Study:
- To extend the existing T measure by proposing a new metric for actor influence.
- To quantify influence based on an actor's success in attracting other significant actors to a network community over time.
Main Methods:
- Developed a novel influence measure based on an actor's attractiveness and connections to other attractors.
- Applied this measure to an empirically collected social network graph.
- Utilized the measure in an influence maximization simulation.
Main Results:
- The proposed measure effectively identifies key actors within a social network.
- Demonstrated the application of the new influence metric in determining optimal seeds for information diffusion.
Conclusions:
- The extended influence measure accurately models actors who draw others into community activity.
- This approach is valuable for identifying key spreaders in information diffusion simulations, aligning with Independent Cascade (IC) models.
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