Since Sept. 11, 2001, there has been great interest in the military and intelligence communities in using Social Network Analysis (SNA) to support the disruption and destruction of global terrorist networks. SNA results, however, tend to be descriptive and are limited due to the lack of advantageous properties of the relationship measures applied to the arcs in a social network. Further, SNA techniques generally focus on a single network context while real relationships are based in multiple contexts. This thesis develops a new proxy measure of pair-wise potential influence between members of a network, a Holistic Interpersonal Influence Measure (HIIM). The HIIM considers the topology of the multiple formal and informal networks to which group members belong as well as non-network characteristics such as age and education level that may indicate potential influence. The HIIM, once constructed results in a network of pair-wise potential influence between group members. Further, the numeric properties of the HIIM are appropriate for use in Operations Research Network Flow models, which will enable analysts to provide prescriptive analysis focused on specific actions and their outcomes. In addition to an overall measure of influence, the HIIM methodology provides important intermediate results such as the development of operational group profiles. The methodology is applied to open source data on both Al Qaeda and the Jemaah Islamiah (JI) terrorist networks. Key leaders are identified, and leadership profiles are developed. Further, a parametric analysis is performed to compare influence based on individual characteristics, network topology characteristics, and mixtures of network and non-network characteristics.