### Abstract

We consider social networks in which information propagates directionally across layers of rational agents. Each agent makes a locally optimal estimate of the state of the world, and communicates this estimate to agents downstream. When agents receive some information from a common source their estimates are correlated. We show that the resulting redundancy can lead to the loss of information about the state of the world across layers of the network, even when all agents have full knowledge of the network's structure. A simple algebraic condition identifies networks in which information loss occurs, and we show that all such networks must contain a particular network motif. We also study random networks asymptotically as the number of agents increases, and find a sharp transition in the probability of information loss at the point at which the number of agents in one layer exceeds the number in the previous layer.

Original language | English (US) |
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Pages (from-to) | 448-469 |

Number of pages | 22 |

Journal | Journal of Complex Networks |

Volume | 6 |

Issue number | 3 |

DOIs | |

State | Published - Jul 1 2018 |

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### ASJC Scopus subject areas

- Computer Networks and Communications
- Management Science and Operations Research
- Control and Optimization
- Computational Mathematics
- Applied Mathematics

### Cite this

*Journal of Complex Networks*,

*6*(3), 448-469. https://doi.org/10.1093/comnet/cnx032

**Loss of information in feedforward social networks.** / Stolarczyk, Simon; Bhardwaj, Manisha; Bassler, Kevin E.; Ma, Wei Ji; Josić, Krešimir.

Research output: Contribution to journal › Article

*Journal of Complex Networks*, vol. 6, no. 3, pp. 448-469. https://doi.org/10.1093/comnet/cnx032

}

TY - JOUR

T1 - Loss of information in feedforward social networks

AU - Stolarczyk, Simon

AU - Bhardwaj, Manisha

AU - Bassler, Kevin E.

AU - Ma, Wei Ji

AU - Josić, Krešimir

PY - 2018/7/1

Y1 - 2018/7/1

N2 - We consider social networks in which information propagates directionally across layers of rational agents. Each agent makes a locally optimal estimate of the state of the world, and communicates this estimate to agents downstream. When agents receive some information from a common source their estimates are correlated. We show that the resulting redundancy can lead to the loss of information about the state of the world across layers of the network, even when all agents have full knowledge of the network's structure. A simple algebraic condition identifies networks in which information loss occurs, and we show that all such networks must contain a particular network motif. We also study random networks asymptotically as the number of agents increases, and find a sharp transition in the probability of information loss at the point at which the number of agents in one layer exceeds the number in the previous layer.

AB - We consider social networks in which information propagates directionally across layers of rational agents. Each agent makes a locally optimal estimate of the state of the world, and communicates this estimate to agents downstream. When agents receive some information from a common source their estimates are correlated. We show that the resulting redundancy can lead to the loss of information about the state of the world across layers of the network, even when all agents have full knowledge of the network's structure. A simple algebraic condition identifies networks in which information loss occurs, and we show that all such networks must contain a particular network motif. We also study random networks asymptotically as the number of agents increases, and find a sharp transition in the probability of information loss at the point at which the number of agents in one layer exceeds the number in the previous layer.

UR - http://www.scopus.com/inward/record.url?scp=85050769498&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050769498&partnerID=8YFLogxK

U2 - 10.1093/comnet/cnx032

DO - 10.1093/comnet/cnx032

M3 - Article

VL - 6

SP - 448

EP - 469

JO - Journal of Complex Networks

JF - Journal of Complex Networks

SN - 2051-1310

IS - 3

ER -