| CPC G06Q 30/0255 (2013.01) [G06N 5/022 (2013.01); G06N 20/00 (2019.01); G06Q 30/0201 (2013.01); G06Q 30/0244 (2013.01); G06Q 50/01 (2013.01); H04L 51/52 (2022.05); H04L 67/55 (2022.05); G06N 5/01 (2023.01); G06N 7/01 (2023.01); H04L 51/214 (2022.05)] | 20 Claims |

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1. A method comprising:
receiving a request for an interval of time during which to post a content item on a social network in a plurality of social networks, the interval of time being divided into a first subset of units of time;
creating one or more transformation functions implementing a machine learning engine to profile data based on the social network as a constituent of a first social network against a second social network;
executing instructions at the one or more servers to redefine the interval of time to include a second subset of units of time;
calculating the schedule for posting a content item on the social network and the post-to-reaction filter based on the second subset of units of time;
modeling a decay function as a function of the post-to-reaction filter, the decay function representative of a level of interest of an audience of the user associated with one or more of the first social network and the second social network;
determining an optimal time to post the content item on the social network as a function of the decay function;
recomputing the schedule as a function of the decay function and received schedule for posting the content item on the social network; and
auto-scheduling the posting of the content item to automatically post the content item based on the decay function, wherein auto-scheduling includes one or more of estimating data values representing audience reaction and data values representing domain specific schedule personalization.
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