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Assessing the missing data problem in criminal network analysis using forensic DNA data

Sabine De Moor (UGent) , Christophe Vandeviver (UGent) and Tom Vander Beken (UGent)
(2020) SOCIAL NETWORKS. 61. p.99-106
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Abstract
Missing data is pertinent to criminal networks due to the hidden nature of crime. Generally, researchers evaluate the impact of incomplete network data by extracting or adding nodes and/or edges from a known network. Statistics on this reduced or completed network are then compared with statistics from the known network. In this study, we integrate police data on known offenders with DNA data on unknown offenders. Statistics from the integrated dataset (‘known network’) are compared with statistics from the police data (‘reduced network’). Networks with both known and unknown offenders are bigger but also have a different structure to networks with only known offenders.
Keywords
Sociology and Political Science, General Social Sciences, General Psychology, Anthropology, Missing data, Unknown offenders, Real-world network, Forensic DNA, Police recorded crime data, CENTRALITY MEASURES, SERIAL OFFENDERS, DARK NETWORKS

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Citation

Please use this url to cite or link to this publication:

MLA
De Moor, Sabine, et al. “Assessing the Missing Data Problem in Criminal Network Analysis Using Forensic DNA Data.” SOCIAL NETWORKS, vol. 61, 2020, pp. 99–106.
APA
De Moor, S., Vandeviver, C., & Vander Beken, T. (2020). Assessing the missing data problem in criminal network analysis using forensic DNA data. SOCIAL NETWORKS, 61, 99–106.
Chicago author-date
De Moor, Sabine, Christophe Vandeviver, and Tom Vander Beken. 2020. “Assessing the Missing Data Problem in Criminal Network Analysis Using Forensic DNA Data.” SOCIAL NETWORKS 61: 99–106.
Chicago author-date (all authors)
De Moor, Sabine, Christophe Vandeviver, and Tom Vander Beken. 2020. “Assessing the Missing Data Problem in Criminal Network Analysis Using Forensic DNA Data.” SOCIAL NETWORKS 61: 99–106.
Vancouver
1.
De Moor S, Vandeviver C, Vander Beken T. Assessing the missing data problem in criminal network analysis using forensic DNA data. SOCIAL NETWORKS. 2020;61:99–106.
IEEE
[1]
S. De Moor, C. Vandeviver, and T. Vander Beken, “Assessing the missing data problem in criminal network analysis using forensic DNA data,” SOCIAL NETWORKS, vol. 61, pp. 99–106, 2020.
@article{8633833,
  abstract     = {Missing data is pertinent to criminal networks due to the hidden nature of crime. Generally, researchers evaluate the impact of incomplete network data by extracting or adding nodes and/or edges from a known network. Statistics on this reduced or completed network are then compared with statistics from the known network. In this study, we integrate police data on known offenders with DNA data on unknown offenders. Statistics from the integrated dataset (‘known network’) are compared with statistics from the police data (‘reduced network’). Networks with both known and unknown offenders are bigger but also have a different structure to networks with only known offenders.},
  author       = {De Moor, Sabine and Vandeviver, Christophe and Vander Beken, Tom},
  issn         = {0378-8733},
  journal      = {SOCIAL NETWORKS},
  keywords     = {Sociology and Political Science,General Social Sciences,General Psychology,Anthropology,Missing data,Unknown offenders,Real-world network,Forensic DNA,Police recorded crime data,CENTRALITY MEASURES,SERIAL OFFENDERS,DARK NETWORKS},
  language     = {eng},
  pages        = {99--106},
  title        = {Assessing the missing data problem in criminal network analysis using forensic DNA data},
  url          = {http://dx.doi.org/10.1016/j.socnet.2019.09.003},
  volume       = {61},
  year         = {2020},
}

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