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Simulation to find user behavior impact in social media network

  • US 9,485,319 B1
  • Filed: 12/30/2015
  • Issued: 11/01/2016
  • Est. Priority Date: 12/30/2015
  • Status: Expired due to Fees
First Claim
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1. A computer-implemented method for determining an impact of a behavior of at least one user in a social media network, the method comprising:

  • obtaining, by a processor, at least one characteristic describing the behavior of the user in a simulation of the social media network;

    determining by the processor, via use of a time series based modeler which uses a linear regression method, a first function of the at least one characteristic, wherein the first function describes a first model of a behavior of the simulated social media network with respect to time;

    changing, by the processor, the at least one characteristic to obtain at least one changed characteristic;

    determining by the processor, via use of a time series based modeler which uses a linear regression method, a second function of the at least one changed characteristic, wherein the second function describes a second model of the behavior of the simulated social media network with respect to time;

    comparing, by the processor, the first function and the second function over time by using a linear or non-linear least squares method to determine at least one difference in at least one impact duration of time, the at least one impact duration of time being an amount of time during which a volume of messages associated with the second function differs, after a point of substantial equality, from a volume of messages associated with the first function;

    determining, by the processor, a simulated amount of an effect of the difference in at least one impact duration of time at each of a plurality of nodes within one or more levels of the social media network; and

    outputting, by the processor, data indicative of the determined simulated amount of the effect of the difference in at least one impact duration of time at each of the plurality of nodes within one or more levels of the social media network.

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