A natural language processing artificial intelligence network and data security system comprising: a processor; a memory storing machine readable instructions; wherein the processor is to execute the machine readable instructions to: detect interactions of a user in a dataset using natural language processing, wherein the dataset comprises a plurality of interactions between a plurality of users on a network; determine a plurality of textual features expressed in natural language in each of the interactions; determine a plurality of emotional features for each of the interactions based on the plurality of textual features and an emotions index, wherein the emotions index associates textual features with emotional features; determine an emotional state for each of the interactions based on an aggregation of the plurality of emotional features; determine a chronological sequence of the emotional states for the user based on a time of each of the interactions and the determined emotional state for each of the interactions; determine a probability of transitioning between different emotional states for the user based on the chronological sequence of emotional states for the user; generate an emotions model as a primitive for artificial intelligence based on the probability of transitioning between different emotional states for the user; determine an emotional stability value of the user based on the emotions model; determine using an artificial intelligence network and data security subsystem whether the emotional stability value of the user is within a threshold, wherein the threshold is based on an emotional stability value of other users in the dataset; and in response to the determination that the emotional stability value is within the threshold the artificial intelligence network and data security subsystem regulates network permissions of the user. a processor; a memory storing machine readable instructions; wherein the processor is to execute the machine readable instructions to: detect interactions of a user in a dataset using natural language processing, wherein the dataset comprises a plurality of interactions between a plurality of users on a network; determine a plurality of textual features expressed in natural language in each of the interactions; determine a plurality of emotional features for each of the interactions based on the plurality of textual features and an emotions index, wherein the emotions index associates textual features with emotional features; determine an emotional state for each of the interactions based on an aggregation of the plurality of emotional features; determine a chronological sequence of the emotional states for the user based on a time of each of the interactions and the determined emotional state for each of the interactions; determine a probability of transitioning between different emotional states for the user based on the chronological sequence of emotional states for the user; generate an emotions model as a primitive for artificial intelligence based on the probability of transitioning between different emotional states for the user; determine an emotional stability value of the user based on the emotions model; determine using an artificial intelligence network and data security subsystem whether the emotional stability value of the user is within a threshold, wherein the threshold is based on an emotional stability value of other users in the dataset; and in response to the determination that the emotional stability value is within the threshold the artificial intelligence network and data security subsystem regulates network permissions of the user. detect interactions of a user in a dataset using natural language processing, wherein the dataset comprises a plurality of interactions between a plurality of users on a network; determine a plurality of textual features expressed in natural language in each of the interactions; determine a plurality of emotional features for each of the interactions based on the plurality of textual features and an emotions index, wherein the emotions index associates textual features with emotional features; determine an emotional state for each of the interactions based on an aggregation of the plurality of emotional features; determine a chronological sequence of the emotional states for the user based on a time of each of the interactions and the determined emotional state for each of the interactions; determine a probability of transitioning between different emotional states for the user based on the chronological sequence of emotional states for the user; generate an emotions model as a primitive for artificial intelligence based on the probability of transitioning between different emotional states for the user; determine an emotional stability value of the user based on the emotions model; determine using an artificial intelligence network and data security subsystem whether the emotional stability value of the user is within a threshold, wherein the threshold is based on an emotional stability value of other users in the dataset; and in response to the determination that the emotional stability value is within the threshold the artificial intelligence network and data security subsystem regulates network permissions of the user.