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Inferring social ties across heterogenous networks

Published: 08 February 2012 Publication History

Abstract

It is well known that different types of social ties have essentially different influence on people. However, users in online social networks rarely categorize their contacts into "family", "colleagues", or "classmates". While a bulk of research has focused on inferring particular types of relationships in a specific social network, few publications systematically study the generalization of the problem of inferring social ties over multiple heterogeneous networks. In this work, we develop a framework for classifying the type of social relationships by learning across heterogeneous networks. The framework incorporates social theories into a factor graph model, which effectively improves the accuracy of inferring the type of social relationships in a target network by borrowing knowledge from a different source network. Our empirical study on five different genres of networks validates the effectiveness of the proposed framework. For example, by leveraging information from a coauthor network with labeled advisor-advisee relationships, the proposed framework is able to obtain an F1-score of 90% (8-28% improvements over alternative methods) for inferring manager-subordinate relationships in an enterprise email network.

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cover image ACM Conferences
WSDM '12: Proceedings of the fifth ACM international conference on Web search and data mining
February 2012
792 pages
ISBN:9781450307475
DOI:10.1145/2124295
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 February 2012

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Author Tags

  1. inferring social ties
  2. predictive model
  3. social influence analysis
  4. social network

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  • (2024)Domain-Adaptive Graph Attention-Supervised Network for Cross-Network Edge ClassificationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.330963235:12(17842-17855)Online publication date: Dec-2024
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