599 citations · 1.2k across the 114 of their papers we have counts for
9 papers · 1 filter
DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection
Xuanwen Huang, Yang Yang, Yang Wang +5
Graph Anomaly Detection (GAD) has recently become a hot research spot due to its practicability and theoretical value. Since GAD emphasizes the application and the rarity of anomal…
Political Communities on Twitter: Case Study of the 2022 French Presidential Election
Hadi Abdine, Yanzhu Guo, Virgile Rennard +1
With the significant increase in users on social media platforms, a new means of political campaigning has appeared. Twitter and Facebook are now notable campaigning tools during e…
Can Author Collaboration Reveal Impact? The Case of h-index
Giannis Nikolentzos, George Panagopoulos, Iakovos Evdaimon +1
Scientific impact has been the center of extended debate regarding its accuracy and reliability. From hiring committees in academic institutions to governmental agencies that distr…
Transfer Graph Neural Networks for Pandemic Forecasting
George Panagopoulos, Giannis Nikolentzos, Michalis Vazirgiannis
The recent outbreak of COVID-19 has affected millions of individuals around the world and has posed a significant challenge to global healthcare. From the early days of the pandemi…
Multi-task Learning for Influence Estimation and Maximization
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
We address the problem of influence maximization when the social network is accompanied by diffusion cascades. In prior works, such information is used to compute influence probabi…
Perturb and Combine to Identify Influential Spreaders in Real-World Networks
Antoine J. -P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros +2
Some of the most effective influential spreader detection algorithms are unstable to small perturbations of the network structure. Inspired by bagging in Machine Learning, we propo…
Adaptive Submodular Influence Maximization with Myopic Feedback
Guillaume Salha, Nikolaos Tziortziotis, Michalis Vazirgiannis
This paper examines the problem of adaptive influence maximization in social networks. As adaptive decision making is a time-critical task, a realistic feedback model has been cons…
A k-core Decomposition Framework for Graph Clustering
Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis +4
Graph clustering or community detection constitutes an important task for investigating the internal structure of graphs, with a plethora of applications in several domains. Tradit…
Clustering and Community Detection in Directed Networks: A Survey
Fragkiskos D. Malliaros, Michalis Vazirgiannis
Networks (or graphs) appear as dominant structures in diverse domains, including sociology, biology, neuroscience and computer science. In most of the aforementioned cases graphs a…