A relational event history is determined based on a data set, the relational event history. 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, where the set of sequential decisions includes at least two decisions as to recipients of a relational event, where the probability model includes one or more statistical parameters and corresponding statistics that relate to one or more of senders, modes, topics, or recipients of relational events. A baseline communications behavior for the relational event history is determined based on the populated probability model, the baseline including a first set of values for the one or more statistical parameters, and departures within the relational event history from the baseline communications behavior are determined.
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, wherein the set of sequential decisions comprises at least two decisions as to recipients of a relational event, and 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; 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. 2. The method of claim 1, wherein the at least two decisions as to recipients of the relational event comprise a first decision as to a social context of the communication, and one or more additional decisions as to which actors included within the social context will receive the relational event. 3. The method of claim 2, wherein a first social context includes a first set of actors, and wherein a second social context includes a second set of actors. 4. The method of claim 1, wherein the at least two decisions as to recipients of the communication comprise a first decision by an actor to send the relational event to a first recipient, and a second decision by the actor to send the relational event to a second recipient. 5. The method of claim 1, wherein a set of recipients of the relational event includes less than all of the actors in the set of actors. 6. The method of claim 1, further comprising determining a subset of actors included in the set of actors, wherein at least one decision included in the set of sequential decisions by the actor comprises selecting a recipient of the relational event from the subset of actors. 7. The method of claim 1, wherein determining departures from the baseline communications behavior within the relational event history comprises determining a second set of values for the statistical parameters based on one or more subsets of the relational events included in the relational event history and comparing the second set of values for the statistical parameters to the first set of values. 8. The method of claim 7, wherein comparing the second set of values for the statistical parameters to the first set of values comprises determining a hypothesis regarding communications behavior within the relational event history; and testing the hypothesis using the second set of values. 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: 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, wherein the set of sequential decisions comprises at least two decisions as to recipients of a relational event, and 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; 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. 10. The system of claim 9, wherein the at least two decisions as to recipients of the relational event comprise a first decision as to a social context of the communication, and one or more additional decisions as to which actors included within the social context will receive the relational event. 11. The system of claim 10, wherein a first social context includes a first set of actors, and wherein a second social context includes a second set of actors. 12. The system of claim 9, wherein the at least two decisions as to recipients of the communication comprise a first decision by an actor to send the relational event to a first recipient, and a second decision by the actor to send the relational event to a second recipient. 13. The system of claim 9, wherein a set of recipients of the relational event includes less than all of the actors in the set of actors. 14. The system of claim 9, further comprising determining a subset of actors included in the set of actors, wherein at least one decision included in the set of sequential decisions by the actor comprises selecting a recipient of the relational event from the subset of actors. 15. The system of claim 9, wherein determining departures from the baseline communications behavior within the relational event history comprises determining a second set of values for the statistical parameters based on one or more subsets of the relational events included in the relational event history and comparing the second set of values for the statistical parameters to the first set of values. 16. The system of claim 15, wherein comparing the second set of values for the statistical parameters to the first set of values comprises determining a hypothesis regarding communications behavior within the relational event history; and testing the hypothesis using the second set of values. 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: 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, wherein the set of sequential decisions comprises at least two decisions as to recipients of a relational event, and 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; 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.