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Will Triadic Closure Strengthen Ties in Social Networks?

Published: 23 January 2018 Publication History

Abstract

The social triad—a group of three people—is one of the simplest and most fundamental social groups. Extensive network and social theories have been developed to understand its structure, such as triadic closure and social balance. Over the course of a triadic closure—the transition from two ties to three among three users, the strength dynamics of its social ties, however, are much less well understood. Using two dynamic networks from social media and mobile communication, we examine how the formation of the third tie in a triad affects the strength of the existing two ties. Surprisingly, we find that in about 80% social triads, the strength of the first two ties is weakened although averagely the tie strength in the two networks maintains an increasing or stable trend. We discover that (1) the decrease in tie strength among three males is more sharply than that among females, and (2) the tie strength between celebrities is more likely to be weakened as the closure of a triad than those between ordinary people. Furthermore, we formalize a triadic tie strength dynamics prediction problem to infer whether social ties of a triad will become weakened after its closure. We propose a TRIST method—a kernel density estimation (KDE)-based graphical model—to solve the problem by incorporating user demographics, temporal effects, and structural information. Extensive experiments demonstrate that TRIST offers a greater than 82% potential predictability for inferring triadic tie strength dynamics in both networks. The leveraging of the KDE and structural correlations enables TRIST to outperform baselines by up to 30% in terms of F1-score.

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Published In

cover image ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data  Volume 12, Issue 3
June 2018
360 pages
ISSN:1556-4681
EISSN:1556-472X
DOI:10.1145/3178546
Issue’s Table of Contents
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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Publication History

Published: 23 January 2018
Accepted: 01 October 2017
Revised: 01 May 2017
Received: 01 September 2016
Published in TKDD Volume 12, Issue 3

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Author Tags

  1. Social triad
  2. dynamics
  3. predictive model
  4. tie strength

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  • Research-article
  • Research
  • Refereed

Funding Sources

  • Lindemann Foundation
  • NSFC
  • National Natural Science Foundation of China
  • International Science and Technology Cooperation Program of China

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