Bridging Community Detection and Influence Maximization: A Generalized Approach

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Authors: Máté Vass, Miklós Krész, László Hajdú, András Bóta
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Abstract

Code, Data, and Results for: “Bridging Community Detection and Influence Maximization: A Generalized Approach” This Zenodo record contains the code, data, results, runtime logs, and visualizations associated with the manuscript: “Bridging Community Detection and Influence Maximization: A Generalized Approach”, submitted to Social Network Analysis and Mining, 2026. All materials are provided under a single DOI to support transparency and reproducibility during the peer-review process. Contents The record consists of the following ZIP archives: - code.zip Source code used for data processing, analysis, and generation of results reported in the article. - data.zip Input data used in the study. This may include raw and/or processed datasets as described in the manuscript. - results.zip Output data generated by running the analysis code, including numerical results corresponding to those reported in the paper. - runtimes.zip Runtime logs from code execution, documenting environment configurations, dependencies, and execution behavior. - visualizations.zip Figures, plots, and other visual outputs used in the manuscript and supplementary materials. License - Data & results: CC-BY 4.0 - Code: MIT License

Fields of Study & Subjects

Complex Network Analysis Techniques Opinion Dynamics and Social Influence Digital Marketing and Social Media

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 January 2026
Language
EN