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Locating multiple information sources in social networks based on the naming game
Xue Yang1,2, Zhiliang Zhu1, Hai Yu1
1Software College, Northeastern University, Shenyang 110819, China.
Physics Letters. A
|October 5, 2020
Summary
This study introduces a novel method for identifying multiple information origins in social networks, even without knowing the number of sources. The approach effectively traces information propagation to pinpoint origins.
Area of Science:
- Network Science
- Information Theory
- Computational Social Science
Background:
- Information propagation in social networks is complex.
- Identifying information sources is crucial for controlling information impact.
- Existing methods often require knowing the number of sources.
Purpose of the Study:
- To develop a method for multiple source localization in social networks.
- To address the challenge of source identification without prior knowledge of source count.
- To analyze information propagation using the naming game theory.
Main Methods:
- Utilizing the naming game theory for network observations.
- Segmenting observations into sets based on provided information.
- Estimating the source for each observation set.
- Aggregating set sources to determine all information origins.
Main Results:
- Successfully located multiple information sources without pre-specifying their quantity.
- Demonstrated the method's effectiveness through simulations on four real-world datasets.
- Validated the approach for accurate source estimation in information propagation scenarios.
Conclusions:
- The proposed method provides a robust solution for multiple source localization.
- It overcomes the limitation of needing to know the number of information sources beforehand.
- The technique is effective for understanding information dynamics in social networks.
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