activity
20172026
most citedEfficient Algorithms for Minimizing the Kirchhoff Index via Adding Edges

7 citations · 20 across the 32 of their papers we have counts for

collaborators

45 papers

cs.LG2026

Not Just Oversmoothing: Detecting the Echo Chamber Effect in Graph Neural Networks

Asela Hevapathige, Ahad N. Zehmakan, Asiri Wijesinghe +1

Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that fail to capture the heteroge…

cs.SI2026

JECHO: Scalable Echo Chamber Detection via Jaccard-based Homophily and Seed Expansion

Ali Safarpoor Dehkordi, Atsushi Miyauchi, Francesco Bonchi +1

Detecting echo chambers is critical for understanding and limiting negative social phenomena, such as online polarization, misinformation, and conspiracy theory diffusion. However,…

cs.SI2026

Opinion Polarization in LLM-Based Social Networks: Manipulation and Mitigation

Ali Safarpoor Dehkordi, Mohammad Shirzadi, Ahad N. Zehmakan

How vulnerable are online social networks to adversaries who seek to amplify opinion polarization by manipulating opinions, and how difficult is it to mitigate such manipulation? E…

cs.LG2026

Invariant-Stratified Propagation for Expressive Graph Neural Networks

Asela Hevapathige, Ahad N. Zehmakan, Asiri Wijesinghe +1

Graph Neural Networks (GNNs) face fundamental limitations in expressivity and capturing structural heterogeneity. Standard message-passing architectures are constrained by the 1-di…

cs.SI2026

Efficient Edge Rewiring Strategies for Enhancing PageRank Fairness

Changan Liu, Haoxin Sun, Ahad N. Zehmakan +1

We study the notion of unfairness in social networks, where a group such as females in a male-dominated industry are disadvantaged in access to important information, e.g. job post…

cs.SI2025

Promoting Fairness in Information Access within Social Networks

Changan Liu, Xiaotian Zhou, Ahad N. Zehmakan +1

The advent of online social networks has facilitated fast and wide spread of information. However, some users, especially members of minority groups, may be less likely to receive…