Systems and methods for collation, translation, and analysis of passively created digital interaction and relationship data

A non-transitory computer readable medium containing executable instructions that when executed perform a method of modeling relationships between a plurality of e-mail users comprising:

• extracting a record of e-mail exchanges between the plurality of users, wherein the record is extracted from at least one of an e-mail server and an e-mail transfer agent and wherein the data is extracted through a direct internet access protocol;
• filtering the record to produce relevant interaction data based on e-mail exchanges between two users;
• and
• loading the relevant interaction data into a relationship modeling program, wherein the relationship modeling program assigns a weight to each of a plurality of characteristics of the relevant interaction data, and wherein the relationship modeling program provides a model of relationships between the plurality of e-mail users based at least in part on the weight of each of the plurality of characteristics, wherein the plurality of characteristics comprises interaction volume, interaction volume, interaction frequency, interaction type, number of communication participants, time of first and last interaction, a relationship strength of two users based on the number of exchanges between the two users, a ratio of source to target versus target to source interactions, and a time between interactions, and
• generating relationship data by analyzing the one or more characteristics.

A method of processing relationship data in a server, the method comprising:

• receiving at the server data on one or more characteristics of one or more e-mail exchanges between two users of a digital communication system, wherein the data is transferred to the server from an interaction database, and
• wherein the interaction database is populated through a direct internet access protocol, wherein the one or more characteristics comprises interaction volume, interaction frequency, interaction type, number of communication participants, time of first and last interaction, a relationship strength of two users based on the number of exchanges between the two users, a ratio of source to target versus target to source interactions, and a time between interactions;
• assigning a respective weight to each of the one or more characteristics;
• and transferring from the server the data to a processor for generating relationship data by analyzing the one or more characteristics.