20 citations · 63 across the 13 of their papers we have counts for
7 papers · 1 filter
Network Analysis of Cyberbullying Interactions on Instagram
Satyaki Sikdar, Manuel Sandoval, Taylor Hales +6
Cyberbullying continues to grow in prevalence and its impact is felt by thousands worldwide. This study seeks a network science perspective on cyberbullying interaction patterns on…
Attributed Graph Modeling with Vertex Replacement Grammars
Satyaki Sikdar, Neil Shah, Tim Weninger
Recent work at the intersection of formal language theory and graph theory has explored graph grammars for graph modeling. However, existing models and formalisms can only operate…
The Infinity Mirror Test for Graph Models
Satyaki Sikdar, Daniel Gonzalez Cedre, Trenton W. Ford +1
Graph models, like other machine learning models, have implicit and explicit biases built-in, which often impact performance in nontrivial ways. The model's faithfulness is often m…
Joint Subgraph-to-Subgraph Transitions -- Generalizing Triadic Closure for Powerful and Interpretable Graph Modeling
Justus Hibshman, Daniel Gonzalez Cedre, Satyaki Sikdar +1
We generalize triadic closure, along with previous generalizations of triadic closure, under an intuitive umbrella generalization: the Subgraph-to-Subgraph Transition (SST). We pre…
Towards Interpretable Graph Modeling with Vertex Replacement Grammars
Justus Hibshman, Satyaki Sikdar, Tim Weninger
An enormous amount of real-world data exists in the form of graphs. Oftentimes, interesting patterns that describe the complex dynamics of these graphs are captured in the form of…
Modeling Graphs with Vertex Replacement Grammars
Satyaki Sikdar, Justus Hibshman, Tim Weninger
One of the principal goals of graph modeling is to capture the building blocks of network data in order to study various physical and natural phenomena. Recent work at the intersec…
Fast Detection of Community Structures using Graph Traversal in Social Networks
Partha Basuchowdhuri, Satyaki Sikdar, Varsha Nagarajan +3
Finding community structures in social networks is considered to be a challenging task as many of the proposed algorithms are computationally expensive and does not scale well for…