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Bipartite Network Model for Inferring Hidden Ties in Crime Data

Haruna Isah, Daniel Neagu, Paul Trundle
2015 Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15  
Our contributions are twofold: we propose a bipartite network model for inferring hidden ties between actors who initiated an illegal interaction and objects affected by the interaction, we then validate  ...  the method in two case studies on pharmaceutical crime and underground forum data using standard network algorithms for structural and community analysis.  ...  order to evaluate how we can infer ties among criminals using bipartite network modelling.  ... 
doi:10.1145/2808797.2808842 dblp:conf/asunam/IsahNT15 fatcat:76zbeoxukbb2rjvdd5naley5ui

AI and Deep Learning for Urban Computing [chapter]

Senzhang Wang, Jiannong Cao
2021 The Urban Book Series  
AbstractIn the big data era, with the large volume of available data collected by various sensors deployed in urban areas and the recent advances in AI techniques, urban computing has become increasingly  ...  In this chapter, we introduce the challenges, methodologies, and applications of AI techniques for urban computing.  ...  Wang et al. (2016a, b) proposed to use a coupled hidden Markov model for road-network-level traffic-congestion estimation.  ... 
doi:10.1007/978-981-15-8983-6_43 fatcat:uq7j3hvsvzfl5lq33omx64un3i

Locating Central Actors in Co-offending Networks

Mohammad A. Tayebi, Laurens Bakker, Uwe Glasser, Vahid Dabbaghian
2011 2011 International Conference on Advances in Social Networks Analysis and Mining  
In this paper, firstly we introduce a data model, called unified crime data model to bridge the conceptual gap between abstract crime data level and co-offending network mining level.  ...  Using this data model, we extract the co-offending network of five years real-world crime data.  ...  We are also grateful for technical support from the ICURS Institute at Simon Fraser University.  ... 
doi:10.1109/asonam.2011.120 dblp:conf/asunam/TayebiBGD11 fatcat:l4b6pjgrcncufb4m3nih4yjqxq

Temporal similarity metrics for latent network reconstruction: The role of time-lag decay [article]

Hao Liao, Ming-Kai Liu, Manuel Sebastian Mariani, Mingyang Zhou, Xingtong Wu
2019 arXiv   pre-print
Our findings shed new light on the notion of similarity between pairs of nodes in complex networks.  ...  network reconstruction.  ...  We compare their performance in reconstructing the whole propagation network in both synthetic and real data.  ... 
arXiv:1904.02413v1 fatcat:q6lfuiymvbbyndpvehgphuso6e

The role of motifs in understanding behavior in social and engineered networks

Kun Tu, Dave Braines, Diane Felmlee, Don Towsley, Roger Whitaker, Liam Turner, James Llinas, Timothy P. Hanratty
2018 Next-Generation Analyst VI  
Graphs can also model behavior in engineered systems, and internal network structures can significantly affect dynamic behavior.  ...  networks inter-operate in positive ways.  ...  Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1117/12.2309471 fatcat:jhxdvhouxvdxhpiclqzianju2i

Temporal dynamics in covert networks

Chiara Broccatelli, Martin Everett, Johan Koskinen
2016 Methodological Innovations  
In this article, we extend the use of dynamic line-graphs to bipartite networks for incorporating time directly into the network, and we suggest an alternative way to visualise the evolution of actors'  ...  After illustrating our method, we present some examples of its use on real-world data for visualising network evolutions over time.  ...  Gerdes for sharing their data sets. The authors are also grateful to the anonymous reviewers who provided many valuable comments and suggestions.  ... 
doi:10.1177/2059799115622766 fatcat:derf4hyzojf6fdayevpz42tgjq

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

Nicola Lettieri, Antonio Altamura, Rosalba Giugno, Alfonso Guarino, Delfina Malandrino, Alfredo Pulvirenti, Francesco Vicidomini, Rocco Zaccagnino
2018 Future Internet  
Data mining, machine learning, simulations and other computational methods lie today at the hearth of the scientific endeavour in a growing number of social research areas from anthropology to economics  ...  In this scenario, an increasingly important role is played by analytical platforms: integrated environments allowing researchers to experiment cutting-edge data-driven and computation-intensive analyses  ...  Acknowledgments: The authors are truly thankful to Margherita Vestoso for the help given in proofreading of the article.  ... 
doi:10.3390/fi10050037 fatcat:r3y5uqk5zrbybfgmlwzdu3yh6i

Criminal Network Community Detection Using Graphical Analytic Methods: A Survey

Theyvaa Sangkaran, Azween Abdullah, NZ. JhanJhi
2018 EAI Endorsed Transactions on Energy Web  
The concept of community was vividly discussed as well as the algorithms for detecting communities within a network.  ...  Most importantly, a strict review of researches based on the detection of community in a criminal network was carried out revealing the strength and limitations of criminal network community detection  ...  Results showed that the implemented maximum-likelihood method correctly inferred the number of communities available for each network data, thereby revealing the strength of the method for making safe  ... 
doi:10.4108/eai.13-7-2018.162690 fatcat:objcbuwp4bamlcr7asc4r3ejzq

Threats from the Dark: A Review over Dark Web Investigation Research for Cyber Threat Intelligence

Randa Basheer, Bassel Alkhatib, Zhiyong Xu
2021 Journal of Computer Networks and Communications  
In this review, we probe recent studies in the field of analyzing Dark Web content for Cyber Threat Intelligence (CTI), introducing a comprehensive analysis of their techniques, methods, tools, approaches  ...  Researching in the Dark Web proved to be an essential step in fighting cybercrime, whether with a standalone investigation of the Dark Web solely or an integrated one that includes contents from the Surface  ...  On the actors' side, they constructed a bipartite author-thread network, projecting it with the authors' network to infer hackers' co-occurrences in a unified network. Pastrana et al.  ... 
doi:10.1155/2021/1302999 fatcat:w2kg4s2tsfholbf5lctv6wlzjm

Identifying Key-Players in Online Activist Groups on the Facebook Social Network

Mariam Nouh, Jason R. C. Nurse
2015 2015 IEEE International Conference on Data Mining Workshop (ICDMW)  
Additionally, we aim to identify the most influential users in the group and infer their relationship strength.  ...  In this paper, we utilise Social Network Analysis (SNA) techniques to understand the dynamics of the interaction between users in a Facebookbased activist group.  ...  ACKNOWLEDGMENT The authors would like to thank the Ministry of Education and King Abdulaziz City for Science and Technology (KACST), Saudi Arabia for financially sponsoring and supporting Mariam Nouh's  ... 
doi:10.1109/icdmw.2015.88 dblp:conf/icdm/NouhN15 fatcat:tr36gkocqrbt7hrlfi6k2td4ce

Corruption and complexity: a scientific framework for the analysis of corruption networks

Issa Luna-Pla, José R. Nicolás-Carlock
2020 Applied Network Science  
Thus, in this article we present an empirical approach to model corruption using the concepts and tools of complexity science, mainly, complex networks science.  ...  Under this framework, we describe a major corruption scandal that took place in Mexico involving a network of hundreds of shell companies used to embezzle billions of dollars.  ...  Authors' contributions Both authors conceived the study, participated in the design of it, the analysis of the data, and drafted the manuscript. All authors read and approved the final manuscript.  ... 
doi:10.1007/s41109-020-00258-2 fatcat:fg7cq2iaubd6lktiujh66htmmm

Embedding Ranking-Oriented Recommender System Graphs [article]

Taher Hekmatfar, Saman Haratizadeh, Sama Goliaei
2020 arXiv   pre-print
Ranking-oriented GRSs that form a major class of recommendation systems, mostly use the graphical representation of preference (or rank) data for measuring node similarities, from which they can infer  ...  The resulting embedding are then used for predicting users' unknown pairwise preferences from which the final recommendation lists are inferred.  ...  @ = ∑ 2 − 1 log ( + 1) =1 (2) m4: (Drama-Crime, 1994) This data could be modeled as a heterogeneous graph like the one in Figure 4 . Figure 4.  ... 
arXiv:2007.16173v1 fatcat:qawnlsqipvdovooavsssj7osay

Quick survey of graph-based fraud detection methods [article]

Paul Irofti, Andrei Patrascu, Andra Baltoiu
2021 arXiv   pre-print
We present a survey on anomaly detection techniques used for fraud detection that exploit both the graph structure underlying the data and the contextual information contained in the attributes.  ...  In these networks, fraudulent behaviour may appear as a distinctive graph edge, such as spam message, a node or a larger subgraph structure, such as when a group of clients engage in money laundering schemes  ...  The approach in [71] considers tensors for modelling large scale networked data.  ... 
arXiv:1910.11299v3 fatcat:zyupd4ezxrgw3f7g5utzihy6qi

Networks beyond pairwise interactions: Structure and dynamics

Federico Battiston, Giulia Cencetti, Iacopo Iacopini, Vito Latora, Maxime Lucas, Alice Patania, Jean-Gabriel Young, Giovanni Petri
2020 Physics reports  
We review the measures designed to characterize the structure of these systems and the models proposed to generate synthetic structures, such as random and growing bipartite graphs, hypergraphs and simplicial  ...  Here we present a complete overview of the emerging field of networks beyond pairwise interactions.  ...  For applications of inference methods of higher-order interactions on real brain networks data, see Section 9.2.  ... 
doi:10.1016/j.physrep.2020.05.004 fatcat:pkugz4i5obainmcrwod6i4od7q

Networks beyond pairwise interactions: structure and dynamics [article]

Federico Battiston, Giulia Cencetti, Iacopo Iacopini, Vito Latora, Maxime Lucas, Alice Patania, Jean-Gabriel Young, Giovanni Petri
2020 arXiv   pre-print
, bipartite graphs and hypergraphs.  ...  We review the measures designed to characterize the structure of these systems and the models proposed in the literature to generate synthetic structures, such as random and growing simplicial complexes  ...  This inference technique has been used to, for instance, infer the latent geometry of bipartite networks of metabolites and of the reactions they intervene in [203] .  ... 
arXiv:2006.01764v1 fatcat:h4ezvequxrbyrozpjbb6lbqhj4
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