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The Influence of Technology on Social Network Analysis and Mining

  • Book
  • © 2013

Overview

Editors:
  1. Tansel Özyer

    1. Department of Computer Engineering, TOBB University, Sogutozu Ankara, Turkey

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  2. Jon Rokne

    1. Computer Science, University of Calgary, Calgary, Canada

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  3. Gerhard Wagner

    1. IPSC, European Commission Joint Research Cent., Ispra, Italy

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  4. Arno H.P. Reuser

    1. Leiden, Netherlands

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  • Provides applications of social network analysis Provides insights into cyber anthropology Covers influential aspects of social media in numerous contexts
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Social Networks (LNSN)

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Table of contents (28 chapters)

  1. Front Matter

    Pages i-xxiii
    Download chapter PDF

  2. EgoClustering: Overlapping Community Detection via Merged Friendship-Groups

    • Bradley S. Rees, Keith B. Gallagher
    Pages 1-20

  3. Optimization Techniques for Multiple Centrality Computations

    • Christian von der Weth, Klemens Böhm, Christian Hütter
    Pages 21-47

  4. Application of Social Network Metrics to a Trust-Aware Collaborative Model for Generating Personalized User Recommendations

    • Iraklis Varlamis, Magdalini Eirinaki, Malamati Louta
    Pages 49-74

  5. TweCoM: Topic and Context Mining from Twitter

    • Luca Cagliero, Alessandro Fiori
    Pages 75-100

  6. Pixel-Oriented Network Visualization: Static Visualization of Change in Social Networks

    • Klaus Stein, René Wegener, Christoph Schlieder
    Pages 101-127

  7. Building Expert Recommenders from Email-Based Personal Social Networks

    • Verónica Rivera-Pelayo, Simone Braun, Uwe V. Riss, Hans Friedrich Witschel, Bo Hu
    Pages 129-156

  8. A Local Structure-Based Method for Nodes Clustering: Application to a Large Mobile Phone Social Network

    • Alina Stoica, Zbigniew Smoreda, Christophe Prieur
    Pages 157-184

  9. Virus Propagation Modeling in Facebook

    • Wei Fan, Kai-Hau Yeung
    Pages 185-199

  10. Comparing and Visualizing the Social Spreading of Products on a Large Social Network

    • PÃ¥l Roe Sundsøy, Johannes Bjelland, Geoffrey Canright, Kenth Engø-Monsen, Rich Ling
    Pages 201-225

  11. Engagingness and Responsiveness Behavior Models on the Enron Email Network and Its Application to Email Reply Order Prediction

    • Byung-Won On, Ee-Peng Lim, Jing Jiang, Loo-Nin Teow
    Pages 227-253

  12. Efficient Extraction of High-Betweenness Vertices from Heterogeneous Networks

    • Wen Haw Chong, Wei Shan Belinda Toh, Loo Nin Teow
    Pages 255-273

  13. Cross-Domain Analysis of the Blogosphere for Trend Prediction

    • Patrick Siehndel, Fabian Abel, Ernesto Diaz-Aviles, Nicola Henze, Daniel Krause
    Pages 275-301

  14. Informative Value of Individual and Relational Data Compared Through Business-Oriented Community Detection

    • Vincent Labatut, Jean-Michel Balasque
    Pages 303-330

  15. Clustering Social Networks Using Distance-Preserving Subgraphs

    • Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan
    Pages 331-349

  16. Extraction of Spatio-Temporal Data for Social Networks

    • Judith Gelernter, Dong Cao, Kathleen M. Carley
    Pages 351-372

  17. Detecting Communities in Massive Networks Efficiently with Flexible Resolution

    • Qi Ye, Bin Wu, Bai Wang
    Pages 373-392

  18. Detecting Emergent Behavior in a Social Network of Agents

    • Mohammad Moshirpour, Shimaa M. El-Sherif, Behrouz H. Far, Reda Alhajj
    Pages 393-409

  19. Factors Enabling Information Propagation in a Social Network Site

    • Matteo Magnani, Danilo Montesi, Luca Rossi
    Pages 411-426

  20. Learning from the Past: An Analysis of Person Name Corrections in the DBLP Collection and Social Network Properties of Affected Entities

    • Florian Reitz, Oliver Hoffmann
    Pages 427-453
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About this book

The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding General areas of interest to the book include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

Editors and Affiliations

  • Department of Computer Engineering, TOBB University, Sogutozu Ankara, Turkey

    Tansel Özyer

  • Computer Science, University of Calgary, Calgary, Canada

    Jon Rokne

  • IPSC, European Commission Joint Research Cent., Ispra, Italy

    Gerhard Wagner

  • Leiden, Netherlands

    Arno H.P. Reuser

Bibliographic Information

  • Book Title: The Influence of Technology on Social Network Analysis and Mining

  • Editors: Tansel Özyer, Jon Rokne, Gerhard Wagner, Arno H.P. Reuser

  • Series Title: Lecture Notes in Social Networks

  • DOI: https://doi.org/10.1007/978-3-7091-1346-2

  • Publisher: Springer Vienna

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Wien 2013

  • Hardcover ISBN: 978-3-7091-1345-5Published: 29 March 2013

  • Softcover ISBN: 978-3-7091-1705-7Published: 12 April 2015

  • eBook ISBN: 978-3-7091-1346-2Published: 15 March 2013

  • Series ISSN: 2190-5428

  • Series E-ISSN: 2190-5436

  • Edition Number: 1

  • Number of Pages: XXIII, 643

  • Topics: Computer Science, general

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