Social scientists have begun to collect large datasets that are heterogeneous and semi-structured, but the ability to analyze such data has lagged behind its collection. We design a process to map such datasets to a numerical form, apply singular value decomposition clustering, and explore the impact of individual attributes or fields by overlaying visualizations of the clusters. This provides a new path for understanding such datasets, which we illustrate with three real-world examples: the Global Terrorism Database, which records details of every terrorist attack since 1970; a Chicago police dataset, which records details of every drug-related incident over a period of approximately a month; and a dataset describing members of a Hezbollah crime/terror network in the U.S.
|Title of host publication||Security by Design|
|Subtitle of host publication||Innovative Perspectives on Complex Problems|
|Editors||Anthony J. Masys|
|Number of pages||11|
|Publication status||Published - 2018|
|Name||Advanced Sciences and Technologies for Security Applications|