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Walk Prediction in Directed Networks

  • Chuankai An
  • A. James O’Malley
  • Daniel N. Rockmore
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 812)

Abstract

In this paper we consider the problem of directed and walk-specific spread of information in complex social networks. Traditional models tend to explain “explosive” information spreading on social media (e.g., Twitter) – a broadcast or epidemiological kind of model with a focus on the sequence of newly “infected” nodes generated from a source node to multiple targets. However, the process of (single-track) information flow, wherein there is a node-by-node (and not necessarily a newly visited node) trajectory of information transfer is also a common phenomenon. A key example of interest is the sequence of physician visits of a given patient (a referral sequence) in a physician network, wherein the patient is a carrier of information about treatment or disease. With this motivation in mind, we present a Bayesian Personalized Ranking (BPR) model to predict the next node on a walk of a given network navigator using features derived from network analysis. This problem is related to but different from the well-studied problem of link prediction. We apply our model to data from several years of U.S. patient referrals. We present experiments showing that the adoption of network-based features in the BPR framework improves hit-rate and mean percentile rank for next-node prediction.

Keywords

Information walk prediction Network measures Bayesian personalized ranking Patient referral network 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Chuankai An
    • 1
  • A. James O’Malley
    • 2
  • Daniel N. Rockmore
    • 3
    • 4
  1. 1.Department of Computer ScienceDartmouth CollegeHanoverUSA
  2. 2.Department of Biomedical Data Science and the Dartmouth Institute of Health Policy and Clinical Practice in the Geisel School of MedicineDartmouth CollegeLebanonUSA
  3. 3.Departments of Computer Science and MathematicsDartmouth CollegeHanoverUSA
  4. 4.External Faculty of the Santa Fe InstituteSanta FeUSA

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