### Abstract

Certain real-life networks have a community structure in which communities overlap. For example, a typical bus network includes bus stops (nodes), which belong to one or more bus lines (communities) that often overlap. Clearly, it is important to take this information into account when measuring the centrality of a bus stop-how important it is to the functioning of the network. For example, if a certain stop becomes inaccessible, the impact will depend in part on the bus lines that visit it. However, existing centrality measures do not take such information into account. Our aim is to bridge this gap. We begin by developing a new game-Theoretic solution concept, which we call the Configuration semivalue, in order to have greater flexibility in modelling the community structure compared to previous solution concepts from cooperative game theory. We then use the new concept as a building block to construct the first extension of Closeness centrality to networks with community structure (overlapping or otherwise). Despite the computational complexity inherited from the Configuration semivalue, we show that the corresponding extension of Closeness centrality can be computed in polynomial time. We empirically evaluate this measure and our algorithm that computes it by analysing the Warsaw public transportation network.

Original language | English (US) |
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Title of host publication | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |

Publisher | AAAI press |

Pages | 622-629 |

Number of pages | 8 |

ISBN (Electronic) | 9781577357605 |

State | Published - Jan 1 2016 |

Event | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States Duration: Feb 12 2016 → Feb 17 2016 |

### Other

Other | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |
---|---|

Country | United States |

City | Phoenix |

Period | 2/12/16 → 2/17/16 |

### Fingerprint

### ASJC Scopus subject areas

- Artificial Intelligence

### Cite this

*30th AAAI Conference on Artificial Intelligence, AAAI 2016*(pp. 622-629). AAAI press.

**Closeness centrality for networks with overlapping community structure.** / Tarkowski, Mateusz K.; Szczepański, Piotr; Rahwan, Talal; Michalak, Tomasz P.; Wooldridge, Michael.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*30th AAAI Conference on Artificial Intelligence, AAAI 2016.*AAAI press, pp. 622-629, 30th AAAI Conference on Artificial Intelligence, AAAI 2016, Phoenix, United States, 2/12/16.

}

TY - GEN

T1 - Closeness centrality for networks with overlapping community structure

AU - Tarkowski, Mateusz K.

AU - Szczepański, Piotr

AU - Rahwan, Talal

AU - Michalak, Tomasz P.

AU - Wooldridge, Michael

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Certain real-life networks have a community structure in which communities overlap. For example, a typical bus network includes bus stops (nodes), which belong to one or more bus lines (communities) that often overlap. Clearly, it is important to take this information into account when measuring the centrality of a bus stop-how important it is to the functioning of the network. For example, if a certain stop becomes inaccessible, the impact will depend in part on the bus lines that visit it. However, existing centrality measures do not take such information into account. Our aim is to bridge this gap. We begin by developing a new game-Theoretic solution concept, which we call the Configuration semivalue, in order to have greater flexibility in modelling the community structure compared to previous solution concepts from cooperative game theory. We then use the new concept as a building block to construct the first extension of Closeness centrality to networks with community structure (overlapping or otherwise). Despite the computational complexity inherited from the Configuration semivalue, we show that the corresponding extension of Closeness centrality can be computed in polynomial time. We empirically evaluate this measure and our algorithm that computes it by analysing the Warsaw public transportation network.

AB - Certain real-life networks have a community structure in which communities overlap. For example, a typical bus network includes bus stops (nodes), which belong to one or more bus lines (communities) that often overlap. Clearly, it is important to take this information into account when measuring the centrality of a bus stop-how important it is to the functioning of the network. For example, if a certain stop becomes inaccessible, the impact will depend in part on the bus lines that visit it. However, existing centrality measures do not take such information into account. Our aim is to bridge this gap. We begin by developing a new game-Theoretic solution concept, which we call the Configuration semivalue, in order to have greater flexibility in modelling the community structure compared to previous solution concepts from cooperative game theory. We then use the new concept as a building block to construct the first extension of Closeness centrality to networks with community structure (overlapping or otherwise). Despite the computational complexity inherited from the Configuration semivalue, we show that the corresponding extension of Closeness centrality can be computed in polynomial time. We empirically evaluate this measure and our algorithm that computes it by analysing the Warsaw public transportation network.

UR - http://www.scopus.com/inward/record.url?scp=85007154622&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85007154622&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85007154622

SP - 622

EP - 629

BT - 30th AAAI Conference on Artificial Intelligence, AAAI 2016

PB - AAAI press

ER -