Method and apparatus for modeling a population to predict individual behavior using location data from social network messages

A non-transitory computer-readable medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform operations for predicting a location behavior of at least one individual, the operations comprising:

• receiving a plurality of social networking messages having spatial location data and user identification information;
• filtering the plurality of social networking messages to remove one or more of the plurality of social networking messages that are not related to mobility of a user to create a filtered plurality of social networking messages;
• creating a population model by applying a kernel density estimation to the filtered plurality of social networking messages;
• creating an individual model for each different user identification by applying the kernel density estimation to a subset of the filtered plurality of social networking messages for the each different user identification;
• and
• generating a probability density function map that predicts the location behavior of the at least one individual using a mixture model based upon the individual model of the at least one individual and the population model.

A method for predicting a location behavior of at least one individual, comprising:

• receiving, by a processor, a plurality of social networking messages within a region having global positioning satellite coordinates and user identification information;
• filtering, by the processor, the plurality of social networking messages to remove one or more of the plurality of social networking messages that are not related to mobility of a user to create a filtered plurality of social networking messages;
• creating, by the processor, a population model by applying a kernel density estimation to the filtered plurality of social networking messages;
• creating, by the processor, an individual model for each different user identification by applying the kernel density estimation to a subset of the filtered plurality of social networking messages for the each different user identification;
• and
• generating, by the processor, a probability density function map that predicts the location behavior of the at least one individual as a percentage value in a plurality of different locations within the region and outside of the region using a mixture model based upon the individual model of the at least one individual and the population model, wherein the mixture model weights the population model greater as a number of data points used for the individual model decreases.