20 citations · 58 across the 42 of their papers we have counts for
49 papers
Alex Meiburg
The existential theory of the reals asks whether polynomial constraints with integer coefficients have a real solution. We give a proof placing this problem in the counting hierarc…
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…
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,…
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…
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…
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…
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…
Quantifying and Minimizing Perception Gap in Social Networks
Hemant Kumar Gehlot, Mohammad Shirzadi, Junhao Gan +1
Social media has transformed global communication, yet its network structure can systematically distort perceptions through effects like the majority illusion and echo chambers. We…
Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily
Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan
Graph Neural Networks (GNNs) have achieved significant success in addressing node classification tasks. However, the effectiveness of traditional GNNs degrades on heterophilic grap…
Adaptive Initial Residual Connections for GNNs with Theoretical Guarantees
Mohammad Shirzadi, Ali Safarpoor Dehkordi, Ahad N. Zehmakan
Message passing is the core operation in graph neural networks, where each node updates its embeddings by aggregating information from its neighbors. However, in deep architectures…
Opinion Dynamics: A Comprehensive Overview
Mohammad Shirzadi, Emilio Cruciani, Ahad N. Zehmakan
Opinion dynamics, the evolution of individuals through social interactions, is an important area of research with applications ranging from politics to marketing. Due to its interd…
Efficient Algorithms for Computing Random Walk Centrality
Changan Liu, Zixuan Xie, Ahad N. Zehmakan +1
Random walk centrality is a fundamental metric in graph mining for quantifying node importance and influence, defined as the weighted average of hitting times to a node from all ot…
Graph Neural Diffusion via Generalized Opinion Dynamics
Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan
There has been a growing interest in developing diffusion-based Graph Neural Networks (GNNs), building on the connections between message passing mechanisms in GNNs and physical di…
Graph-based Fake Account Detection: A Survey
Ali Safarpoor Dehkordi, Ahad N. Zehmakan
In recent years, there has been a growing effort to develop effective and efficient algorithms for fake account detection in online social networks. This survey comprehensively rev…
The Impact of External Sources on the Friedkin-Johnsen Model
Charlotte Out, Sijing Tu, Stefan Neumann +1
To obtain a foundational understanding of timeline algorithms and viral content in shaping public opinions, computer scientists started to study augmented versions of opinion forma…
Efficient Algorithms for Minimizing the Kirchhoff Index via Adding Edges
Xiaotian Zhou, Ahad N. Zehmakan, Zhongzhi Zhang
The Kirchhoff index, which is the sum of the resistance distance between every pair of nodes in a network, is a key metric for gauging network performance, where lower values signi…
Depth-Adaptive Graph Neural Networks via Learnable Bakry-'Emery Curvature
Asela Hevapathige, Ahad N. Zehmakan, Qing Wang
Graph Neural Networks (GNNs) have demonstrated strong representation learning capabilities for graph-based tasks. Recent advances on GNNs leverage geometric properties, such as cur…
More Efficient Sybil Detection Mechanisms Leveraging Resistance of Users to Attack Requests
Ali Safarpoor Dehkordi, Ahad N. Zehmakan
We investigate the problem of sybil (fake account) detection in social networks from a graph algorithms perspective, where graph structural information is used to classify users as…
DeepSN: A Sheaf Neural Framework for Influence Maximization
Asela Hevapathige, Qing Wang, Ahad N. Zehmakan
Influence maximization is key topic in data mining, with broad applications in social network analysis and viral marketing. In recent years, researchers have increasingly turned to…
A Generalisation of Voter Model: Influential Nodes and Convergence Properties
Abhiram Manohara, Ahad N. Zehmakan
Consider an undirected graph G, representing a social network, where each node is blue or red, corresponding to positive or negative opinion on a topic. In the voter model, in disc…
Do Stubborn Users Always Cause More Polarization and Disagreement? A Mathematical Study
Mohammad Shirzadi, Ahad N. Zehmakan
We study how the stubbornness of social network users influences opinion polarization and disagreement. Our work is in the context of the popular Friedkin-Johnson opinion formation…
Fast Query of Biharmonic Distance in Networks
Changan Liu, Ahad N. Zehmakan, Zhongzhi Zhang
The \textit{biharmonic distance} (BD) is a fundamental metric that measures the distance of two nodes in a graph. It has found applications in network coherence, machine learning,…
A First Principles Approach to Trust-Based Recommendation Systems in Social Networks
Paras Stefanopoulos, Sourin Chatterjee, Ahad N. Zehmakan
This paper explores recommender systems in social networks which leverage information such as item rating, intra-item similarities, and trust graph. We demonstrate that item-rating…
Viral Marketing in Social Networks with Competing Products
Ahad N. Zehmakan, Xiaotian Zhou, Zhongzhi Zhang
Consider a directed network where each node is either red (using the red product), blue (using the blue product), or uncolored (undecided). Then in each round, an uncolored node ch…