The analysis of information diffusion in social media networks: A comparative experimental study
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Date
2021
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UNIVERSITY MOHAMED BOUDIAF M'SILA - FACULTY of Mathematics and Computer Science - DEPARTMENT: Computer Science
Abstract
Social influence is the science that studies how people's ideas, attitudes and actions may be changed in combination with Social Network Analysis (SNA) where relationships and flows are important to map and measure. The problem of this research is influence and information diffusion. This analysis is based on the Linear Threshold Model and the Independent Cascade Model (ICM) using a dataset (network): the Facebook user’s is based on its structure (size, type and diameter, components) and type of relationships. Network metrics and visualization were manipulated by Gephi as well. Finally, the findings of our experiments indicate that the selection of the starting nodes has a major effect on the diffusion process. and (LTM) model gives more nodes active than (ICM) model.
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Keywords
Social Network Analysis (SNA), information diffusion, influence