© 2014

Measuring Scholarly Impact

Methods and Practice

  • Ying Ding
  • Ronald Rousseau
  • Dietmar Wolfram


  • Provides a complete guide to analyzing scholarly communication and the informetrics used for the assessment of scholarly impact

  • Consolidates techniques and technologies for measuring scholarly impact from the fields of statistical science, scientific visualization, network analysis, text mining and information retrieval

  • Equips data scientists with the ability to apply these techniques and technologies to other social network analyses and metrics-related research


Table of contents

  1. Front Matter
    Pages i-xiv
  2. Network Tools and Analysis

    1. Front Matter
      Pages 1-1
    2. Ludvig Bohlin, Daniel Edler, Andrea Lancichinetti, Martin Rosvall
      Pages 3-34
    3. Raf Guns
      Pages 35-55
    4. Staša Milojević
      Pages 57-82
    5. Ludo Waltman, Erjia Yan
      Pages 83-100
  3. The Science System

  4. Statistical and Text-Based Methods

  5. Visualization

    1. Front Matter
      Pages 283-283
    2. Nees Jan van Eck, Ludo Waltman
      Pages 285-320
    3. Katy Börner, David E. Polley
      Pages 321-341
  6. Back Matter
    Pages 343-346

About this book


This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.


ISI Page Rank Thomson Reuters bibliometrics citations community detection discrete choice models impact factor informetrics knowledge integration and diffusion network dynamics percentiles and effect size scholarly impact scientometrics system life cycle text mining topic modeling visualization

Editors and affiliations

  • Ying Ding
    • 1
  • Ronald Rousseau
    • 2
  • Dietmar Wolfram
    • 3
  1. 1.School of Informatics and ComputingIndiana UniversityBloomingtonUSA
  2. 2.University of AntwerpAntwerpBelgium
  3. 3.University of Wisconsin-MilwaukeeMilwaukeeUSA

Bibliographic information

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