1 code implementation • 23 Nov 2024 • Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao
The region2vec methods generate node neural embeddings based on attribute similarity, geographic adjacency and spatial interactions, and then extract network communities based on node embeddings using agglomerative clustering.
2 code implementations • 10 Oct 2022 • Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao
Community Detection algorithms are used to detect densely connected components in complex networks and reveal underlying relationships among components.
7 code implementations • 27 Aug 2020 • Yuhao Kang, Song Gao, Yunlei Liang, Mingxiao Li, Jinmeng Rao, Jake Kruse
Understanding dynamic human mobility changes and spatial interaction patterns at different geographic scales is crucial for monitoring and measuring the impacts of non-pharmaceutical interventions (such as stay-at-home orders) during the pandemic.
Social and Information Networks Physics and Society
no code implementations • 23 Apr 2020 • Song Gao, Jinmeng Rao, Yuhao Kang, Yunlei Liang, Jake Kruse, Doerte Doepfer, Ajay K. Sethi, Juan Francisco Mandujano Reyes, Jonathan Patz, Brian S. Yandell
The emergence of SARS-CoV-2 and the coronavirus infectious disease (COVID-19) has become a pandemic.
Social and Information Networks Physics and Society Populations and Evolution 65D10 H.4; G.3; J.2
no code implementations • 9 Apr 2020 • Song Gao, Jinmeng Rao, Yuhao Kang, Yunlei Liang, Jake Kruse
To contain the Coronavirus disease (COVID-19) pandemic, one of the non-pharmacological epidemic control measures in response to the COVID-19 outbreak is reducing the transmission rate of SARS-COV-2 in the population through (physical) social distancing.
Physics and Society Social and Information Networks Populations and Evolution H.4; H.5
1 code implementation • 24 Mar 2020 • Yunlei Liang, Song Gao, Yuxin Cai, Natasha Zhang Foutz, Lei Wu
In this research, we present a time-aware dynamic Huff model (T-Huff) for location-based market share analysis and calibrate this model using large-scale store visit patterns based on mobile phone location data across ten most populated U. S. cities.
Social and Information Networks H.1