Citation

Morris JF, Deckro RF. Behav. Sci. Terrorism Polit. Aggres. 2013; 5(2): 70-93.

Copyright

(Copyright © 2013, Informa - Taylor and Francis Group)

DOI

10.1080/19434472.2012.731696

PMID

unavailable

Abstract

Social network analysis (SNA) conclusions are drawn on terrorist and dark network data sets that may provide erroneous results due to an indeterminate amount of missing data or data corruption. Compounding these effects, information sources reporting on terrorist groups and other dark network organizations may intentionally or unintentionally provide false data. These introduced errors may be significant as they could produce analytic results that are counter to the true situation, leading to misappropriation of resources, improper strategy adoption, and erroneous actions. Analyst cognizance of the causes of imperfect social network data, the importance of proper boundary specification, biases introduced via the employed data collection methods, and characteristics of social network information sources, particularly inherent informant accuracy assumptions, are necessary for SNA analysts to ascertain the resultant social network model's limitations and the inferences that can properly be drawn from the analysis. Specific to investigating terrorist groups and dark networks, trusted and deceptive social network information sources are introduced.