Search Results for author:
Found 10 papers, 5 papers with code
Synwalk -- Community Detection via Random Walk Modelling
We thoroughly validate the effectiveness of our approach on synthetic and empirical networks, respectively, and compare Synwalk's performance with the performance of Infomap and Walktrap.
Structack: Structure-based Adversarial Attacks on Graph Neural Networks
In this work, we study adversarial attacks that are uninformed, where an attacker only has access to the graph structure, but no information about node attributes.
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks
We hope our findings raise awareness about this issue in our community and lay a foundation for the future development of GNN models that are more robust to such attacks.
On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks
In this work, we systematically study the impact of community structure on the performance of GNNs in semi-supervised node classification on graphs.
Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictions
Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions.
Computers and Society
How Users Explore Ontologies on the Web: A Study of NCBO's BioPortal Usage Logs
In particular, we were able to identify seven distinct browsing-behavior types, which all make use of different functionality provided by BioPortal.
Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering
In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering.
Surfacing Estimation Uncertainty in the Decay Parameters of Hawkes Processes with Exponential Kernels
With a series of experiments with synthetic and real-world data from domains such as "classical" earthquake modeling or the manifestation of collective emotions on Twitter, we demonstrate that our proposed approach helps to quantify uncertainty and thereby to understand and fit Hawkes processes in practice.
RFID-based Article-to-Fixture Predictions in Real-World Fashion Stores
Additionally, we conduct a pilot to investigate the challenges related to the integration of such a localization system in the day-to-day business of retail stores.
Recommendation Fairness in Social Networks Over Time
We further study how interventions on network properties influence fairness by examining counterfactual scenarios with alternative evolution outcomes and differing network properties.
