A method for selecting a third-party from a plurality of third-parties by tunable monitoring of computer security threats to the plurality of third-parties and/or computer security threats from the plurality of third-parties, the method comprising:
- receiving, at a hardware processor operating on a computer, a request from a first entity, to select a third-party, from a plurality of third-parties, to satisfy an entity condition;
- mining and retrieving, by an application programming interface, a plurality of publicly-available artifacts, each artifact, included in the plurality of publicly-available artifacts, comprising:
- a specified third-party, said specified third-party being selected from the plurality of third-parties;
- an artifact source, said artifact source being one or more entities included in a plurality of entities or an anonymous entity;
- and a communication mode, said communication mode being selected from the group consisting of emails, instant messaging service messages, short messaging service messages and chats;
- organizing the plurality of artifacts into a plurality of artifact groups, each artifact group corresponding to one third-party, included in the plurality of third parties, removing one or more artifacts, from each artifact group included in the plurality of artifact groups, that include the anonymous entity as the artifact source, removing one or more artifacts, from each artifact group, included in the plurality of artifact groups, that correspond to a subset of entities that share less than a predetermined number of entity characteristics with the first entity;
- linguistically processing each artifact within each artifact group by:
- accessing an electronic key word and phrase library to characterize sentiment of each key word and/or phrase included in the artifact;
- accessing an electronic emoticon and emoji library to characterize sentiment of each emoji and/or emoticon included in the artifact;
- calculating a number of characters within the artifact;
- and calculating a response time between the artifact and related artifacts;
- generating, using a multi-dimensional scoring scale, a sentiment vector for each linguistically processed artifact within each artifact group, the sentiment vector identifies a correspondence between the linguistically processed artifact to the following emotions:
- intelligent, promoted, positive, encouraged, satisfied, happy, calm, assurance, unintelligent, prevented, negative, aggravated, frustrated, sad, anger and fear;
- combining, for each artifact group, the sentiment vectors generated for each linguistically processed artifact, into a combined sentiment vector;
- assigning, based on the combined sentiment vector, a sentiment score for each artifact group that corresponds to each of the third-parties, a higher sentiment score indicates positive sentiment, and a lower sentiment score indicates negative sentiment;
- receiving, at the hardware processor, the sentiment score for each of the plurality of third-parties;
- selecting, at the hardware processor, the third-party, from the plurality of third-parties, said third-party corresponding to the artifact group assigned a highest sentiment score, said third-party being identified as a selected third-party, the highest sentiment score indicating that the selected third-party is associated with more positive sentiment than the remaining third-parties included in the plurality of third-parties;
- for the selected third-party, selecting a most positive communication mode, from the group consisting of emails, instant messaging service messages, short messaging service messages and chats, that is most effective for communication between the selected third-party and the first entity, said selecting comprising:
- organizing, linguistically processed artifacts and assigned sentiment vectors, by communication mode;
- aggregating the sentiment vectors for each communication mode;
- and identifying the most positive sentiment vector;
- and selecting the most positive communication mode associated with the most positive sentiment vector;
- initiating, at the hardware processor, by the first entity, a relationship between the first entity and the selected third-party;
- routing communications between the selected third-party and the first entity on the most positive communication mode;
- determining, at the hardware processor, by the first entity, a scope of the a relationship between the first entity and the selected third-party;
- determining, at the hardware processor, by the first entity, a plurality of relationship characteristics relating to the relationship;
- mining, by the first entity, publicly-available data to determine public sentiment relating to the relationship characteristics;
- identifying, by the first entity, public sentiment relating to the publicly-available data;
- generating, by the first entity, a second score of the public sentiment relating to the publicly-available data;
- maintaining the relationship when the second score is less than a predetermined threshold;
- and dissolving the relationship when the second score is greater than a predetermined threshold.