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Tie strength dynamics over temporal co-authorship social networks

Published: 23 August 2017 Publication History

Abstract

In co-authorship social networks, nodes are authors linked by co-authorship interactions. As time is a relevant aspect of such interactions, concepts and metrics designed to static networks have to be adapted to temporal networks. Tie strength is one of those concepts. Here, we verify if current tie strength definitions are valid for temporal networks by analyzing the strength of ties dynamism over temporal co-authorship networks. Surprisingly, our results show that most ties, even the strong ones, tend to perish over time. Thus, most co-authorships are symbiotic without positive concerns. Also, real co-authorship social networks from different research areas have more weak and random ties than strong and bridge ties.

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  • (2020)Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading modelInternational Journal of Modern Physics C10.1142/S012918312050034531:02(2050034)Online publication date: 21-Jan-2020
  • (2018)Social-Based Classification of Multiple Interactions in Dynamic Attributed Networks2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8621936(4063-4072)Online publication date: Dec-2018

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cover image ACM Conferences
WI '17: Proceedings of the International Conference on Web Intelligence
August 2017
1284 pages
ISBN:9781450349512
DOI:10.1145/3106426
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 the author(s) 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: 23 August 2017

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Author Tags

  1. data and graph mining
  2. temporal social networks analyses
  3. tie strength

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WI '17 Paper Acceptance Rate 118 of 178 submissions, 66%;
Overall Acceptance Rate 118 of 178 submissions, 66%

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View all
  • (2021)On the dynamics of political discussions on Instagram: A network perspectiveOnline Social Networks and Media10.1016/j.osnem.2021.10015525(100155)Online publication date: Sep-2021
  • (2020)Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading modelInternational Journal of Modern Physics C10.1142/S012918312050034531:02(2050034)Online publication date: 21-Jan-2020
  • (2018)Social-Based Classification of Multiple Interactions in Dynamic Attributed Networks2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8621936(4063-4072)Online publication date: Dec-2018

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