Measuring Scholarly Impact: Methods and Practice

✍ Scribed by Ying Ding, Ronald Rousseau, Dietmar Wolfram (eds.)

• Publisher: Springer International Publishing
• Year: 2014
• Tongue: English
• Leaves: 351
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiv
Front Matter....Pages 1-1
Community Detection and Visualization of Networks with the Map Equation Framework....Pages 3-34
Link Prediction....Pages 35-55
Network Analysis and Indicators....Pages 57-82
PageRank-Related Methods for Analyzing Citation Networks....Pages 83-100
Front Matter....Pages 101-101
Systems Life Cycle and Its Relation with the Triple Helix....Pages 103-125
Spatial Scientometrics and Scholarly Impact: A Review of Recent Studies, Tools, and Methods....Pages 127-146
Researchers’ Publication Patterns and Their Use for Author Disambiguation....Pages 147-167
Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence....Pages 169-190
Front Matter....Pages 191-191
Limited Dependent Variable Models and Probabilistic Prediction in Informetrics....Pages 193-214
Text Mining with the Stanford CoreNLP....Pages 215-234
Topic Modeling: Measuring Scholarly Impact Using a Topical Lens....Pages 235-257
The Substantive and Practical Significance of Citation Impact Differences Between Institutions: Guidelines for the Analysis of Percentiles Using Effect Sizes and Confidence Intervals....Pages 259-281
Front Matter....Pages 283-283
Visualizing Bibliometric Networks....Pages 285-320
Replicable Science of Science Studies....Pages 321-341
Back Matter....Pages 343-346

✦ Subjects

Information Storage and Retrieval; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Data Mining and Knowledge Discovery; Computing Methodologies; Visualization