4. The method according to claim 1 , said evidence nodes comprising different dialogue variables used by said personality node, said mood nodes, and said emotion nodes.
1. A method comprising: automatically monitoring communications using a specialized language processor, said communications comprising computerized text forming a conversation conducted between at least two conversation partners, said conversation partners comprising an agent using a specialized language processor and a user, said conversation comprising multiple turns of text utterances exchanged between said conversation partners relating to a specific issue; automatically analyzing said communications using said specialized language processor to simultaneously determine, for said conversation, mental state variables of said user, said mental state variables comprising: an emotion of said user; a mood of said user; and a personality of said user; and automatically aggregating said emotion, said mood, and said personality using a hierarchical probabilistic graphical model that determines a highest probability path through a directed probabilistic graph to infer said mental state of said user, using said specialized language processor, said directed probabilistic graph comprising a single personality node that maintains a single unchanging state, multiple mood nodes, multiple emotion nodes, and multiple evidence nodes, and each of said mood nodes, said emotion nodes, and said evidence nodes being for a different time portion of said conversation; automatically and constantly updating said mental state of said user output from said specialized language processor during said conversation by maintaining, in said directed probabilistic graph, a single unchanging state for said personality for all of said conversation, and maintaining multiple changing states for said emotion and said mood as said conversation progresses to track said mental state of said user during said conversation; automatically and constantly updating said mental state of said user output from said specialized language processor as said specialized language processor tracks said mental state of said user during said conversation; and automatically and constantly displaying said mental state to said agent through a graphic user interface as said mental state is constantly updated during said conversation.