Deception detection on social media: A source-based perspective
Fast, open, free, and accessible, online social networks are massively used to share news
and various information. Unfortunately, their explosive growth amplifies the dissemination of …
and various information. Unfortunately, their explosive growth amplifies the dissemination of …
Revisiting fair-PAC learning and the axioms of cardinal welfare
C Cousins - International Conference on Artificial …, 2023 - proceedings.mlr.press
Cardinal objectives serve as intuitive targets in fair machine learning by summarizing utility
(welfare) or disutility (malfare) $ u $ over $ g $ groups. Under standard axioms, all welfare …
(welfare) or disutility (malfare) $ u $ over $ g $ groups. Under standard axioms, all welfare …
Dismantling complex networks by a neural model trained from tiny networks
J Zhang, B Wang - Proceedings of the 31st ACM International …, 2022 - dl.acm.org
Can we employ one neural model to efficiently dismantle many complex yet unique
networks? This article provides an affirmative answer. Diverse real-world systems can be …
networks? This article provides an affirmative answer. Diverse real-world systems can be …
Onbra: Rigorous estimation of the temporal betweenness centrality in temporal networks
In network analysis, the betweenness centrality of a node informally captures the fraction of
shortest paths visiting that node. The computation of the betweenness centrality measure is …
shortest paths visiting that node. The computation of the betweenness centrality measure is …
Estimation and update of betweenness centrality with progressive algorithm and shortest paths approximation
N Xiang, Q Wang, M You - Scientific Reports, 2023 - nature.com
Betweenness centrality is one of the key measures of the node importance in a network.
However, it is computationally intractable to calculate the exact betweenness centrality of …
However, it is computationally intractable to calculate the exact betweenness centrality of …
Efficient centrality maximization with Rademacher averages
L Pellegrina - Proceedings of the 29th ACM SIGKDD Conference on …, 2023 - dl.acm.org
The identification of the set of k most central nodes of a graph, or centrality maximization, is a
key task in network analysis, with various applications ranging from finding communities in …
key task in network analysis, with various applications ranging from finding communities in …
MCRapper: Monte-Carlo Rademacher averages for poset families and approximate pattern mining
“I'm an MC still as honest”–Eminem, Rap God We present MCRapper, an algorithm for
efficient computation of Monte-Carlo Empirical Rademacher Averages (MCERA) for families …
efficient computation of Monte-Carlo Empirical Rademacher Averages (MCERA) for families …
Efficient Betweenness Centrality Computation over Large Heterogeneous Information Networks
Betweenness centrality (BC), a classic measure which quantifies the importance of a vertex
to act as a communication" bridge" between other vertices in the network, is widely used in …
to act as a communication" bridge" between other vertices in the network, is widely used in …
Efficient Exact and Approximate Betweenness Centrality Computation for Temporal Graphs
Betweenness centrality of a vertex in a graph evaluates how often the vertex occurs in the
shortest paths. It is a widely used metric of vertex importance in graph analytics. While …
shortest paths. It is a widely used metric of vertex importance in graph analytics. While …
SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds
L Pellegrina, F Vandin - … Transactions on Knowledge Discovery from Data, 2023 - dl.acm.org
“Sim Sala Bim!”—Silvan, https://en. wikipedia. org/wiki/Silvan_ (illusionist) Betweenness
centrality is a popular centrality measure with applications in several domains and whose …
centrality is a popular centrality measure with applications in several domains and whose …