CASE: A comprehensive and interactive influence analysis system for social networks (Demo)

Publication Type

Conference Proceeding Article

Publication Date

5-2026

Abstract

The rapid growth of social networks has made social influence analysis a critical research area. Despite significant progress, existing social influence analysis systems face two crucial limitations: insufficient functionality and inadequate interactivity. This highlights the need for a comprehensive system capable of supporting diverse influence analysis tasks while enabling interactive, multi-dimensional exploration of influence dynamics. In this demonstration, we present Case, a comprehensive and interactive influence analysis system for social networks. Case integrates three fundamental influence analysis functionalities: influence maximization, influence minimization, and the most-influenced community search, offering a holistic approach for understanding influence dynamics. It features (i) flexible model configuration supporting six distinct combinations of influence propagation and probability models; (ii) advanced algorithmic frameworks for seed node set selection, blocking node identification, and efficient community search; and (iii) transparent and interactive analysis that allows users to understand diffusion mechanisms and explore alternative intervention strategies. We demonstrate that Case provides an extensive suite of interactive visualization and analysis tools, achieving superior performance in real-world scenarios.

Discipline

Databases and Information Systems | Social Media

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 42nd IEEE International Conference on Data Engineering (ICDE'26), Montreal, QC, Canada, May 4-8

First Page

4189

Last Page

4192

Identifier

10.1109/ICDE65706.2026.00323

Publisher

IEEE

City or Country

Pistacataway

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