53 citations · 215 across the 12 of their papers we have counts for
13 papers
WBT-BGRL: A Non-Contrastive Weighted Bipartite Link Prediction Model for Inductive Learning
Joel Frank Huarayo Quispe, Lilian Berton, Didier Vega-Oliveros
Link prediction in bipartite graphs is crucial for applications like recommendation systems and failure detection, yet it is less studied than in monopartite graphs. Contrastive me…
Bi-layer voter model: Modeling intolerant/tolerant positions and bots in opinion dynamics
Didier A. Vega-Oliveros, Helder L. C. Grande, Flavio Iannelli +1
The diffusion of opinions in Social Networks is a relevant process for adopting positions and attracting potential voters in political campaigns. Opinion polarization, bias, target…
Explainable Fact-checking through Question Answering
Jing Yang, Didier Vega-Oliveros, Taís Seibt +1
Misleading or false information has been creating chaos in some places around the world. To mitigate this issue, many researchers have proposed automated fact-checking methods to f…
Scalable Fact-checking with Human-in-the-Loop
Jing Yang, Didier Vega-Oliveros, Tais Seibt +1
Researchers have been investigating automated solutions for fact-checking in a variety of fronts. However, current approaches often overlook the fact that the amount of information…
Detecting climate teleconnections with Granger causality
Filipi N Silva, Didier A. Vega-Oliveros, Xiaoran Yan +5
Climate system teleconnections are crucial for improving climate predictability, but difficult to quantify. Standard approaches to identify teleconnections are often based on corre…
Dynamic Community Detection into Analyzing of Wildfires Events
Alessandra Marli, Didier A Vega-Oliveros, Moshé Cotacallapa +3
The study and comprehension of complex systems are crucial intellectual and scientific challenges of the 21st century. In this scenario, network science has emerged as a mathematic…
Spatiotemporal data analysis with chronological networks
Leonardo N. Ferreira, Didier A. Vega-Oliveros, Moshe Cotacallapa +4
The amount and size of spatiotemporal data sets from different domains have been rapidly increasing in the last years, which demands the development of robust and fast methods to a…
Measuring the engagement level in encrypted group conversations by using temporal networks
Moshe Cotacallapa, Lilian Berton, Leonardo N. Ferreira +4
Chat groups are well-known for their capacity to promote viral political and marketing campaigns, spread fake news, and create rallies by hundreds of thousands on the streets. Also…
Global Fire Season Severity Analysis and Forecasting
Leonardo N. Ferreira, Didier A. Vega-Oliveros, Liang Zhao +2
In this paper, we divide the globe into a hexagonal grid and we extracted time series of daily fire counts from each cell to estimate and analyze worldwide fire season severity (FS…
From spatio-temporal data to chronological networks: An application to wildfire analysis
Didier A. Vega-Oliveros, Moshé Cotacallapa, Leonardo N. Ferreira +4
Network theory has established itself as an appropriate tool for complex systems analysis and pattern recognition. In the context of spatiotemporal data analysis, correlation netwo…
The Impact of Social Curiosity on Information Spreading on Networks
Didier A. Vega-Oliveros, Lilian Berton, Federico Vazquez +1
Most information spreading models consider that all individuals are identical psychologically. They ignore, for instance, the curiosity level of people, which may indicate that the…
Influence maximization by rumor spreading on correlated networks through community identification
Didier A. Vega-Oliveros, Luciano da Fontoura Costa, Francisco Aparecido Rodrigues
The identification of the minimal set of nodes that maximizes the propagation of information is one of the most relevant problems in network science. In this paper, we introduce a…
Rumor propagation with heterogeneous transmission in social networks
Didier A. Vega-Oliveros, Luciano da F. Costa, Francisco A. Rodrigues
Rumor models consider that information transmission occurs with the same probability between each pair of nodes. However, this assumption is not observed in social networks, which…