Behavioral language computing, in essence, means employing natural language processing (NLP) techniques to calculate the behaviors indicated within the text. This allows for the construction of behavioral models and simulations, with the aim of revealing complex behavioral patterns and social phenomena. This study categorizes behavioral language computing into two major aspects: behavioral language modeling and behavioral language simulation. Regarding behavioral language modeling, the primary task is to pinpoint the actor of the behavior expressed in the language, like discerning who is conducting a particular activity. Subsequently, it’s crucial to identify various behavior attributes, such as its spatial and temporal features. Eventually, we have to recognize the specific behavior events, for example, launching a cyber-attack or taking a policy-related action. As for behavioral language simulation, it consists of five essential elements. First is behavioral planning, which is about formulating the action strategy or plan. Second is accessing and making use of the memory of the entity involved in the behavior. Third is reflecting upon the behavior and making enhancements according to the insights acquired. Fourth is the interaction between the entity and the environment, making sure that the behaviors can adapt to external circumstances. Finally, the fifth element is the implementation of specific actions that make up the behavior.