Predicting relevant empty spots in social interaction

An empty spot refers to an empty hard-to-fill space which can be found in the records of the social interaction, and is the clue to the persons in the underlying social network who do not appear in the records. This contribution addresses a problem to predict relevant empty spots in social interaction. Homogeneous and inhomogeneous networks are studied as a model underlying the social interaction. A heuristic predictor function approach is presented as a new method to address the problem. Simulation experiment is demonstrated over a homogeneous network. A test data in the form of baskets is generated from the simulated communication. Precision to predict the empty spots is calculated to demonstrate the performance of the presented approach.Comment: 11 pages, 5 figures, submitted to J. Systems Science and Complexit

Jrl Syst Sci & Complexity (*) *: 1–11 PREDICTING RELEVANT EMPTY SPOTS IN SOCIAL INTERACTION

Abstract An empty spot refers to an empty hard-to-fill space which can be found in the records of the social interaction, and is the clue to the persons in the underlying social network who do not appear in the records. This contribution addresses a problem to predict relevant empty spots in social interaction. Homogeneous and inhomogeneous networks are studied as a model underlying the social interaction. A heuristic predictor function method is presented as a new method to address the problem. Simulation experiment is demonstrated over a homogeneous network. A test data set in the form of market baskets is generated from the simulated communication. Precision to predict the empty spots is calculated to demonstrate the performance of the presented method

Jrl Syst Sci & Complexity (*) *: 1–11 PREDICTING RELEVANT EMPTY SPOTS IN SOCIAL INTERACTION

Abstract An empty spot refers to an empty hard-to-fill space which can be found in the records of the social interaction, and is the clue to the persons in the underlying social network who do not appear in the records. This contribution addresses a problem to predict relevant empty spots in social interaction. Homogeneous and inhomogeneous networks are studied as a model underlying the social interaction. A heuristic predictor function approach is presented as a new method to address the problem. Simulation experiment is demonstrated over a homogeneous network. A test data in the form of baskets is generated from the simulated communication. Precision to predict the empty spots is calculated to demonstrate the performance of the presented approach