A relational event history is determined based on a data set, the relational event history including 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 is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event, and where the probability model includes one or more statistical parameters and corresponding statistics. A baseline communications behavior for the relational event history is determined based on the populated probability model, and departures from the baseline communications behavior within the relational event history are determined. Determining departures includes determining and testing a hypothesis regarding communications behavior within the relational event history.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: determining 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 is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event, and wherein the probability model includes one or more statistical parameters and corresponding statistics; determining, by one or more processing devices, 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, wherein determining departures from the baseline communications behavior within the relational event history comprises: selecting a subset of relational events included within the relational event history; determining a second set of values for the statistical parameters based on the subset of relational events; determining a hypothesis regarding communications behavior within the relational event history; and testing the hypothesis using the second set of values. 2. The method of claim 1, wherein the one or more statistics relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events. 3. The method of claim 1, wherein determining the hypothesis regarding communications behavior within the relational event history comprises selecting a set of predictions regarding temporal differencing of communications behavior with respect to one or more of the statistical parameters over a period of time. 4. The method of claim 3, wherein the set of predictions regarding temporal differencing include predictions selected from the group comprising a value of a statistical parameter, a velocity of a statistical parameter, and an acceleration of a statistical parameter. 5. The method of claim 1, wherein testing the hypothesis using the second set of values comprises computing a value of a test statistic based on the second set of values and using the test statistic to determine departures from the baseline communications behavior. 6. The method of claim 5, wherein using the test statistic to determine departures from the baseline communications behavior comprises comparing the value of the test statistic to the hypothesis. 7. The method of claim 1, wherein each value in the second set of values corresponds to a particular relational event included in the subset of relational events. 8. The method of claim 1, wherein the hypothesis relates to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events. 10. 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: determining 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 is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event, and wherein the probability model includes one or more statistical parameters and corresponding statistics; determining, by one or more processing devices, 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, wherein determining departures from the baseline communications behavior within the relational event history comprises: selecting a subset of relational events included within the relational event history; determining a second set of values for the statistical parameters based on the subset of relational events; determining a hypothesis regarding communications behavior within the relational event history; and testing the hypothesis using the second set of values. 11. The system of claim 10, wherein the one or more statistics relate to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events. 12. The system of claim 10, wherein determining the hypothesis regarding communications behavior within the relational event history comprises selecting a set of predictions regarding temporal differencing of communications behavior with respect to one or more of the statistical parameters over a period of time. 13. The system of claim 12, wherein the set of predictions regarding temporal differencing include predictions selected from the group comprising a value of a statistical parameter, a velocity of a statistical parameter, and an acceleration of a statistical parameter. 14. The system of claim 10, wherein testing the hypothesis using the second set of values comprises computing a value of a test statistic based on the second set of values and using the test statistic to determine departures from the baseline communications behavior. 15. The system of claim 14, wherein using the test statistic to determine departures from the baseline communications behavior comprises comparing the value of the test statistic to the hypothesis. 16. The system of claim 10, wherein each value in the second set of values corresponds to a particular relational event included in the subset of relational events. 17. The system of claim 10, wherein the hypothesis relates to one or more of senders of relational events, modes of relational events, topics of relational events, or recipients of relational events. 18. 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: determining 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 is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event, and wherein the probability model includes one or more statistical parameters and corresponding statistics; determining, by one or more processing devices, 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, wherein determining departures from the baseline communications behavior within the relational event history comprises: selecting a subset of relational events included within the relational event history; determining a second set of values for the statistical parameters based on the subset of relational events; determining a hypothesis regarding communications behavior within the relational event history; and testing the hypothesis using the second set of values.