One or more user inputs are received. A relational event history is determined based on a data set, where the relational event history includes a set of relational events that occurred in time among a set of actors. Data is populated in a probability model based on the relational event history, where the probability model includes one or more statistical parameters and corresponding statistics that relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events. Graphical analyses of the relational event history are output based on the one or more user inputs.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving one or more user inputs; determining, by one or more processors, a relational event history based on a data set, the relational event history comprising a set of relational events that occurred in time among a set of actors; populating data in a probability model based on the relational event history, wherein the probability model includes one or more statistical parameters and corresponding statistics that relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events; and outputting, based on the one or more user inputs, graphical analyses of the relational event history. 2. The method of claim 1, wherein the probability model is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event. 3. The method of claim 2, further comprising outputting a formulation of the probability model. 4. The method of claim 2, further comprising: determining a baseline communications behavior for the relational event history based on the populated probability model, wherein the baseline comprises a first set of values for the one or more statistical parameters; and determining departures from the baseline communications behavior within the relational event history. 5. The method of claim 4, further comprising: outputting a graphical analysis of the baseline communications behavior; and outputting one or more graphical analyses of departures from the baseline communications behavior. 6. The method of claim 1, further comprising determining, based on the one or more user inputs, the data set. 7. The method of claim 1, further comprising determining, based on the one or more user inputs, one or more covariates, wherein the probability model includes the one or more covariates. 8. The method of claim 1, further comprising determining, based on the one or more user inputs, one or more statistical parameters, wherein the probability model includes the one or more statistical parameters. 9. A system comprising: one or more processing devices; and one or more non-transitory computer-readable media coupled to the one or more processing devices having instructions stored thereon which, when executed by the one or more processing devices, cause the one or more processing devices to perform operations comprising: receiving one or more user inputs; determining, by one or more processors, a relational event history based on a data set, the relational event history comprising a set of relational events that occurred in time among a set of actors; populating data in a probability model based on the relational event history, wherein the probability model includes one or more statistical parameters and corresponding statistics that relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events; and outputting, based on the one or more user inputs, graphical analyses of the relational event history. 10. The system of claim 9, wherein the probability model is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event. 11. The system of claim 10, further comprising outputting a formulation of the probability model. 12. The system of claim 10, further comprising: determining a baseline communications behavior for the relational event history based on the populated probability model, wherein the baseline comprises a first set of values for the one or more statistical parameters; and determining departures from the baseline communications behavior within the relational event history. 13. The system of claim 12, further comprising: outputting a graphical analysis of the baseline communications behavior; and outputting one or more graphical analyses of departures from the baseline communications behavior. 14. The system of claim 10, further comprising determining, based on the one or more user inputs, the data set. 15. The system of claim 10, further comprising determining, based on the one or more user inputs, one or more covariates, wherein the probability model includes the one or more covariates. 16. The system of claim 10, further comprising determining, based on the one or more user inputs, one or more statistical parameters, wherein the probability model includes the one or more statistical parameters. 17. A non-transitory computer-readable medium embodying one or more instructions thereon which, when executed, cause one or more computer processors to perform steps comprising: receiving one or more user inputs; determining, by one or more processors, a relational event history based on a data set, the relational event history comprising a set of relational events that occurred in time among a set of actors; populating data in a probability model based on the relational event history, wherein the probability model includes one or more statistical parameters and corresponding statistics that relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events; and outputting, based on the one or more user inputs, graphical analyses of the relational event history.