Skip to main content
SpringerLink
Log in
Book cover

Temporal Patterns of Communication in Social Networks

  • Book
  • © 2013

Overview

Authors:
  1. Giovanna Miritello

    1. , Department of Mathematics, Universidad Carlos III de Madrid, Leganes, Spain

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Nominated by Universidad Carlos III de Madrid as an outstanding Ph.D. thesis
  • Reveals new and unexpected features of how complex social networks develop over time
  • Based on data mining of massive records of telephone connections
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Theses (Springer Theses)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (6 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Introduction and Motivations

    • Giovanna Miritello
    Pages 1-8

  3. Social and Communication Networks

    • Giovanna Miritello
    Pages 9-44

  4. Social Strategies in Communication Networks

    • Giovanna Miritello
    Pages 45-84

  5. Predicting Tie Creation and Decay

    • Giovanna Miritello
    Pages 85-106

  6. Information Spreading on Communication Networks

    • Giovanna Miritello
    Pages 107-130

  7. Conclusion, Contributions and Vision for the Future

    • Giovanna Miritello
    Pages 131-143

  8. Back Matter

    Pages 145-153
    Download chapter PDF
Back to top

Keywords

About this book

The main interest of this research has been in understanding and characterizing large networks of human interactions as continuously changing objects. In fact, although many real social networks are dynamic networks whose elements and properties continuously change over time, traditional approaches to social network analysis are essentially static, thus neglecting all temporal aspects. Specifically, we have investigated the role that temporal patterns of human interaction play in three main fields of social network analysis and data mining: characterization of time (or attention) allocation in social networks, prediction of link decay/persistence, and information spreading. In order to address this we analyzed large anonymized data sets of phone call communication traces over long periods of time. Access to these observations was granted by Telefonica Research, Spain. The findings that emerge from our research indicate that the observed heterogeneities and correlations of human temporal patterns of interaction significantly affect the traditional view of social networks, shifting from a very steady to a highly complex entity. Since structure and dynamics are tightly coupled, they cannot be disentangled in the analysis and modeling of human behavior, though traditional models seek to do so. Our results impact not only the way in which social network are traditionally characterized, but more importantly also the understanding and modeling phenomena such as group formation, spread of epidemics, and the dissemination of ideas, opinions and information.

Authors and Affiliations

  • , Department of Mathematics, Universidad Carlos III de Madrid, Leganes, Spain

    Giovanna Miritello

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation