Bibliometric Analysis: Algorithms & Interpretations

VOSviewer Demystified: Mathematical Foundations and Network Interpretations of Bibliometric Analysis

What you'll learn

Define the basics of bibliometric analysis

Introduce the required inputs to conduct bibliometric analysis

Introduce the mathematical foundations for bibliometric analysis

Introduce techniques to analyze the resulting networks

Provide students with engaging, hands-on examples

Requirements

No prerequisites are required for this course

Description

Embark on a comprehensive journey into the realm of bibliometric analysis, where you will unravel the intricacies of this powerful research methodology. This course is designed to equip participants with a solid understanding of the mathematical foundations and network interpretations essential for effective bibliometric analysis.Course Objectives:Define the Basics of Bibliometric Analysis: Explore the fundamental concepts that underpin bibliometric analysis, gaining insights into its purpose.Introduce Required Inputs: Learn to navigate the initial steps of bibliometric analysis by understanding the necessary inputs for a successful study.Explore Mathematical Foundations: Delve into the mathematical underpinnings of bibliometric analysis, gaining a deeper appreciation for the algorithms and calculations involved.Introduce Network Analysis Techniques: Uncover the techniques employed to analyze resulting networks, understanding how to extract meaningful information from complex networksHands-on Examples: Engage in practical, hands-on exercises based on Marvel Cinematic Universe movies to ensure an engaging experience for all participants.By the end of this course, participants will not only grasp the theoretical foundations of bibliometric analysis but also acquire the practical skills needed to navigate and interpret bibliometric networks effectively. Join us on this educational journey to enhance your research capabilities and unlock new insights in your academic or professional pursuits.

Overview

Section 1: Introduction

Lecture 1 Welcome to the course

Lecture 2 Bibliometric Analysis at a glance

Lecture 3 The overall methodology for Bibliometric Analysis

Lecture 4 Setting up VOSviewer

Lecture 5 Explore the dataset

Lecture 6 Activity - Download your own dataset [optional]

Section 2: The construction of Bibliometric Graphs

Lecture 7 Co-authorship graph construction 01

Lecture 8 Co-authorship graph construction 02

Lecture 9 Citation graph construction 01

Lecture 10 Citation graph construction 02

Lecture 11 Co-occurrence graph construction

Lecture 12 Bibliographic Coupling graph construction

Lecture 13 Co-citation graph construction

Section 3: Mathematical Foundations of Bibliometric Graphs

Lecture 14 What should be calculated?

Lecture 15 The size of the node

Lecture 16 Occurrence matrix construction

Lecture 17 Activity - Construct occurrence matrix

Lecture 18 VOSViewer – Occurrence matrix

Lecture 19 The thickness of the link

Lecture 20 Co-occurrence matrix construction

Lecture 21 Activity - Construct co-occurrence matrix

Lecture 22 VOSViewer – Co-occurrence matrix

Lecture 23 Distance-based approach – Normalization

Lecture 24 Distance-based approach – Mapping

Lecture 25 Decision Variables - Mapping

Lecture 26 Objective Function & Constraint - Mapping

Lecture 27 Excel Solver – Mapping

Lecture 28 Excel Solver results explanation and comparison to VOS

Lecture 29 Clustering

Lecture 30 Excel Solver – Clustering

Section 4: Analyzing Bibliometric Graphs

Lecture 31 Centrality Measure

Lecture 32 MCU - Dataset description

Lecture 33 MCU - Co-occurrence analysis

Lecture 34 Creating thesaurus file for co-occurrence analysis

Lecture 35 Activity – Create thesaurus file for authorship analysis

Lecture 36 Co-occurrence analysis – Understand the dataset 01

Lecture 37 Co-occurrence analysis – Understand the dataset 02

Lecture 38 Co-occurrence analysis – Understand the dataset 03

Lecture 39 Co-occurrence analysis – Understand the dataset 04

Lecture 40 Co-occurrence analysis – Understand the dataset 05

Lecture 41 Co-occurrence analysis – Understand the dataset 06

Lecture 42 Activity – Merge all nodes that has the word Asgard

Lecture 43 Co-authorship analysis – Update/ revise the knowledge 01

Lecture 44 Co-authorship analysis – Update/ revise the knowledge 02

Lecture 45 Analyzing the bridges in the network 01

Lecture 46 Analyzing the bridges in the network 02

Lecture 47 Detached cluster

Lecture 48 Other types of networks

Section 5: Wrapping up

Lecture 49 Few concerns to be aware of

Lecture 50 Conclusion

Lecture 51 Resources

Lecture 52 Next steps

Lecture 53 Further reading

This course is primarily tailored for researchers