Human mobility-based synthetic social network generation

Human mobility-based synthetic social network generation
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基于人类流动性的合成社交网络生成

DOI:
10.1145/3557921.3565540
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发表时间:
2022
期刊:
HANIMOB '22: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility
影响因子:
--
通讯作者:
Kavak, Hamdi
Kavak, Hamdi
中科院分区:
--
文献类型:
--
作者:
Gallagher, Ketevan;Kotnana, Srihan;Satishkumar, Sachin;Siripurapu, Kheya;Elarde, Justin;Anderson, Taylor;Züfle, Andreas;Kavak, Hamdi

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基于位置的社交网络(LBSNs)将位置信息和社交网络结合起来,在过去的十年里得到了广泛的研究。主要的研究差距是缺乏可用和权威的社交网络数据集。公开可用的社交网络数据集很小且稀疏,因为只有一小部分人口被捕获在数据集中。因此,网络生成器通常被用来生成社交网络,以综合研究LBSN。在这项工作中,我们提出了一个不断发展的社会网络实现基于代理的模拟生成现实的社交网络。在模拟中,当代理移动到不同的感兴趣的地方时,有机会与其他代理建立社会联系,因为他们访问同一个地方。一个大规模的真实世界的移动数据集通知代理在我们的模拟访问的地方的选择。我们定性地表明,我们的模拟社交网络比传统的社交网络发电机,包括埃尔多安-雷尼,瓦特-斯特罗加茨,巴拉巴西-阿尔伯特更现实。
Location-Based Social Networks (LBSNs) combine location information with social networks and have been studied vividly in the last decade. The main research gap is the lack of available and authoritative social network datasets. Publicly available social network datasets are small and sparse, as only a small fraction of the population is captured in the dataset. For this reason, network generators are often employed to generate social networks to study LBSNs synthetically. In this work, we propose an evolving social network implemented in an agent-based simulation to generate realistic social networks. In the simulation, as agents move to different places of interest have the chance to make social connections with other agents as they visit the same place. A large-scale real-world mobility dataset informs the choice of places that agents visit in our simulation. We show qualitatively that our simulated social networks are more realistic than traditional social network generators, including the Erdos-Renyi, Watts-Strogatz, and Barabasi-Albert.
DOI: 10.1007/s10707-016-0279-5
发表时间: 2018-07-01
期刊: GEOINFORMATICA
影响因子: 2
作者:
Li, Ming;Westerholt, Rene;Zipf, Alexander
通讯作者: Zipf, Alexander
移动数据科学(Dagstuhl 研讨会 22021)
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发表时间: 2022
期刊: Dagstuhl Reports
影响因子: --
作者:
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DOI: 10.14778/3115404.3115407
发表时间: 2017-06-01
影响因子: 2.5
作者:
Liu, Yiding;Tuan-Anh Nguyen Pham;Yuan, Quan
通讯作者: Yuan, Quan