Abstract: Described is a system for producing a causal map from a body of text. The system receives multiple textual documents as input. Pairs of cause-effect phrases are extracted from the textual documents and embedded into a vector space. The embedded data is clustered into clusters using a probabilistic technique. A causal map having nodes and edges is generated from the clusters. Using the causal map, causal connections between clusters are obtained, where each node represents an event and each edge represents a causal relationship between events. The causal map is provided as an interactive graph.

Abstract: A method for issuing control signals in response to sentiment. In some embodiments, the method includes: assigning, to each of a plurality of comments, a respective topic vector of length k; determining whether a largest element of the topic vector of a first comment of the plurality of comments exceeds a weight threshold; in response to the determining that the largest element exceeds the weight threshold, classifying the first comment into a first topic, of k topics, the first topic corresponding to the position, in the topic vector, of the largest element of the topic vector; calculating a first sentiment score; calculating an average sentiment score, based in part on the first sentiment score; determining whether the average sentiment score meets a criterion; and in response to the determining that the criterion is met, generating a control signal, the control signal including a message related to the first topic.

Abstract: A method for issuing control signals in response to sentiment. In some embodiments, the method includes: assigning, to each of a plurality of comments, a respective topic vector of length k; determining whether a largest element of the topic vector of a first comment of the plurality of comments exceeds a weight threshold; in response to the determining that the largest element exceeds the weight threshold, classifying the first comment into a first topic, of k topics, the first topic corresponding to the position, in the topic vector, of the largest element of the topic vector; calculating a first sentiment score; calculating an average sentiment score, based in part on the first sentiment score; determining whether the average sentiment score meets a criterion; and in response to the determining that the criterion is met, generating a control signal, the control signal including a message related to the first topic.

Abstract: Described is a system for guiding opinions of users of a social media network. The system determines a number of control agents to be inserted into a population of users of the social media network. The system also determines a rate at which an expressed opinion of each control agent should change over a period of time. A control strategy is output which includes a control schedule based on the number of control agents to be inserted into the population of users and the rate at which the expressed opinion of each control agent should change over the period of time. Finally, the control schedule is deployed in the social media network.

Abstract: Described is a system for guiding opinions of users of a social media network. The system determines a number of control agents to be inserted into a population of users of the social media network. The system also determines a rate at which an expressed opinion of each control agent should change over a period of time. A control strategy is output which includes a control schedule based on the number of control agents to be inserted into the population of users and the rate at which the expressed opinion of each control agent should change over the period of time. Finally, the control schedule is deployed in the social media network.