[HTML][HTML] Using optimal foraging theory to infer how groups make collective decisions
Studying animal behavior as collective phenomena is a powerful tool for understanding
social processes, including group coordination and decision-making. However, linking …
social processes, including group coordination and decision-making. However, linking …
Learning to represent the evolution of dynamic graphs with recurrent models
Graph representation learning for static graphs is a well studied topic. Recently, a few
studies have focused on learning temporal information in addition to the topology of a graph …
studies have focused on learning temporal information in addition to the topology of a graph …
Variable-lag granger causality and transfer entropy for time series analysis
C Amornbunchornvej, E Zheleva… - ACM Transactions on …, 2021 - dl.acm.org
Granger causality is a fundamental technique for causal inference in time series data,
commonly used in the social and biological sciences. Typical operationalizations of Granger …
commonly used in the social and biological sciences. Typical operationalizations of Granger …
Observing leadership as behavior in teams and herds–An ethological approach to shared leadership research
Abstract Both Shared Leadership Theory and evolutionary theories of leadership emphasize
the role of team-level patterns of influence on team or group success. Yet, most of the …
the role of team-level patterns of influence on team or group success. Yet, most of the …
Variable-lag granger causality for time series analysis
C Amornbunchornvej, E Zheleva… - … Conference on Data …, 2019 - ieeexplore.ieee.org
Granger causality is a fundamental technique for causal inference in time series data,
commonly used in the social and biological sciences. Typical operationalizations of Granger …
commonly used in the social and biological sciences. Typical operationalizations of Granger …
Predictive temporal embedding of dynamic graphs
A Taheri, T Berger-Wolf - Proceedings of the 2019 IEEE/ACM …, 2019 - dl.acm.org
In recent years, substantial effort has been devoted to learning to represent the static graphs
and their substructures. A few studies explored utilizing temporal information available in a …
and their substructures. A few studies explored utilizing temporal information available in a …
[HTML][HTML] An investigation of the impact of COVID-19 on health-related cryptocurrencies using time-varying parameters and impulse responses
T Daglis - Healthcare Analytics, 2023 - Elsevier
This study examines the impact of COVID-19 on health-related cryptocurrencies. More
precisely, we use the variable-Lag time-series (VLT) causality to test whether the pandemic …
precisely, we use the variable-Lag time-series (VLT) causality to test whether the pandemic …
The dynamic relationship of cryptocurrencies with supply chain and logistics stocks–the impact of COVID-19
T Daglis - Journal of Economic Studies, 2022 - emerald.com
Purpose The COVID-19 pandemic is known to have affected the logistics and supply chains;
however, there is no adequate empirical evidence to prove in which way it has affected the …
however, there is no adequate empirical evidence to prove in which way it has affected the …
Predicting influential users in online social network groups
The widespread adoption of Online Social Networks (OSNs), the ever-increasing amount of
information produced by their users, and the corresponding capacity to influence markets …
information produced by their users, and the corresponding capacity to influence markets …
Trajectory is not enough: Hidden following detection
In outdoor crimes such as robbery and kidnapping, suspects generally secretly follow their
victims in public places and then look for opportunities to commit crimes. Video anomaly …
victims in public places and then look for opportunities to commit crimes. Video anomaly …