Deffuant Model Cluster Configurations on Network Ensembles

Simulation outputs for the Deffuant opinion dynamics model across four network ensembles: fully connected, Barabasi-Albert, square lattice, and Erdos-Renyi. The data includes convergence times and cluster configurations for parameter combinations of system size and confidence, with up to 1000 samples per combination. The dataset was created by Hendrik Schawe of the Centre National de la Recherche Scientifique.

Use Cases

• Analyzing phase transitions in opinion formation based on confidence parameter epsilon.
• Comparing cluster size distributions across different network topologies mentioned in the description.
• Studying the scaling behavior of convergence times with system size.
• Validating theoretical predictions of the Deffuant model using the provided simulation samples.

Strengths

• Includes data for four distinct network ensembles (fully connected, BA10, lat3, ER10) enabling comparative analysis.
• Provides up to 1000 samples per parameter combination for statistical robustness.
• Covers a range of system sizes up to N_max=1048576 for the fully connected case.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred from the described format.
• Some parameter values are missing due to non-convergence within a reasonable time.

Provenance

Source

paperswithcode

Collection Method

Computational simulation of the Deffuant model on specified network ensembles.