---
title: "The Game-Theoretic Interaction Index on Social Networks with Applications to Link Prediction and Community Detection"
authors:
  - "Piotr L. Szczepanski"
  - "Aleksy Stanislaw Barcz"
  - "Tomasz P. Michalak"
  - "Talal Rahwan"
doi: ""
url: "https://ijcai.org/proceedings/2015/96"
pdf: "https://ijcai.org/proceedings/2015/0096.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "638-643"
track: "Main Track"
keywords:
---

# The Game-Theoretic Interaction Index on Social Networks with Applications to Link Prediction and Community Detection

Piotr L. Szczepanski, Aleksy Stanislaw Barcz, Tomasz P. Michalak, Talal Rahwan

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 638-643.

## Abstract

Measuring similarity between nodes has been an issue of extensive research in the social network analysis literature. In this paper, we construct anew measure of similarity between nodes based on the game-theoretic interaction index (Grabisch and Roubens, 1997). Despite the fact that, in general, this index is computationally challenging, we show that in our network application it can be computed in polynomial time. We test our measure on two important problems, namely link prediction and community detection, given several real-life networks. We show that, for the majority of those networks, our measure outperforms other local similarity measures from the literature.