The first article that I found that appied SNA to crime really piqued my interests. Bichler, Lim, and Larkin (2012) sought to determine if SNA could offer a complementary theory and empirical methods to crime pattern theory for linking people based on shared activities. They believed that SNA could be applied to identifying relative suspects in a criminal case. In order to test this hypothesis, the researchers used the case of the Green River Killer. The Green River Killer, Gary Ridgeway, was active in the 1980s and 1990s in the Seattle and Tacoma areas of Washignton. He is linked to the murder of 49 different women, but authorities believe that he killed upwards of 90 women. He was finally caught in 2001 and sentenced to life in prison in 2003.
Bichler et al (2012) collected data from 3 different sources. The first source was a journalistic account written by two journalist, Smith and Guillen, that contained interviews with victims’ families, law enforcement, and witness information. Smith and Guillen supplemented this information with official information such as court records. The second source was a book written by the lead detective in the case. It included first had accounts about the investigation and confirmed information from Smith and Guillen. The final source were the court transcripts from Ridgeway’s trial.
The sample population for the study included victims, suspects, witnesses, body finders, locations, and other persons of interest. The final sample included 88 people who were victims, had investigatory involvement, suspects, or family/associates. The sample also included 58 different locations. The nodes in the study were the people and the links were connections to geographic locations where either the bodies were found or last seen locations.
Network observations were taken every 6 months for five of the six analysis phases. The final phases consisted of 30 months of analysis. The researchers observed the density of the network to determine overall network cohesion. Betweenness was also analyzed to identify possible suspects. Finally, the Jaccard Coefficient was analyzed to determine if the network changed every six months of the police investigations.
Analysis of the network revealed that the network increases in size overtime which means that the new information that was gathered changed the actual charcteristics of the network. In addition, developments in the investigation up to the 18 month mark contributed to indetifying people which changed the network structure. After 18 months, the networks stabilized. Even though the structure of the network stabilized, the new information changed the actor level centrality scores. This leads to the most important finding which is related to the betweeness centrality measure. At first on suspect was identified as the main suspect due to his high level of betweenness centrality. However, after the 18 month mark, Ridgeway became the most prominent figure in the network because his betweenness centrality measured 2.4 times higher than the original main suspect.
The methods used in this study this study could be used in cold cases such as the Zodiac Killer to narrow down the number of potential suspects and determine persons of interests who may have information that could help the investigation.
The second article looked at the dark networks that were responsible for the July 7, 2005 and July 21, 2005 London Bombings. Burcher and Whelan (2015) sought to determine how the limitations of SNA on dark networks impacted analysis of the network in a crime intelligence context. In order to do this, greater emphasis was placed on the issue of fuzzy boundaries in the analysis of small dynamic networks.
Data was collected from emails, phones calls, text messages, and face to face meetings between the perpetrators of the bombings. The information was gathered from open sources such as the BBC, CNN, The Guardian, and government reports that came out after the bombings.
The sample consisted of 12 individuals from the July 7 bombing group and the July 25 bombing group. The networks were analyzed separately, by group, and then combined to determine if there were links between the two groups. The networks were analyzed based on the degree and betweenness centralities in order to aid in the identification of fuzzy boaundaries for small group dark networks. The nodes in the network were the individuals and the links were the interactions between them.
The results revealed that one individual, Ibrahim, was the central individual when the two networks were combined . However, when the networks were separated, each network had a different individual who was centa The results also revealed that the way in which the network boundaries are defined influence the findings of an analysis.
Bichler, G., Lim, S., & Larin, E. (2017). Tactical social network analysis: Using affiliation networks to aid serial homicide investigation. Homicide Studies, 21(2), 133-158
Bucher, M. & Whelan, C. (2015) Social network analysis and small ‘dark’ group networks: An analysis of the London bombers and the problem of ‘fuzzy’ boundaries, Global Crime, 16(2), 104-122