NAILS Project

Network Analysis Interface for Literature Studies

Shiroq Al-Megren, PhD

King Saud University

Table of contents

1. Introduction

2. Functionality and Services

3. Analysis Case Study

4. Case Study Output

5. Demonstration

6. Conclusion

1

Introduction

What is a literature review?

• A body of text that aims to review the critical points of currentknowledge on a particular topic.

• A comprehensive survey of publications in a specific field of study orrelated to a particular line of research.

2

What is the purpose of a literature review?

• Establish a theoretical framework for your topic/subject area.• Define key terms, definitions, and terminology.• Identify studies, models, case studies, etc. supporting your topic.• Define or establish your area of study, i.e. your research topic.

3

Three Key Points on Literature Review

• Tell me what the research says (theory).• Tell me how the research was carried out (methodology).• Tell me what is missing, i.e. the gap that your research intends to

fill.

4

Terms to Know

• Citation “A reference to another source, like a published article.”• Systematic Mapping Study “A secondary study that aims at

classification and thematic analysis of earlier research.”

• Bibliometrics “Statistical analysis of written publications, such asbooks or articles.”

• Social Network Analysis “Examining and investigating socialstructures through network theory.”

5

Social Network Analysis

Figure 1: Social Network Analysis for a literature search for ’social network

analysis’.

6

NAILS

• NAILS is a tool for performing statistics and Social Network Analysis(SNA) on citation data.

• Bibliometric Network Analysis “Statistical study of connectionsbetween publications.”

• NAILS is a free software; you can redistribute it and/or modify itunder the terms of the GNU General Public License.

7

Functionality and Services

Serives

• NAILS works on publications available for download from ThomsonReuters Web of Science Core Collection.

• It analyses seven essential variables for each publication, whichincludes the authors, keywords, publication forum, article type, and

cited articles.

• The analysis identifies, for instance, the most cited articles andauthors, most common keywords, and journals with most

publications.

8

Services (cont.)

• The analysis and statistics are accompanied with visualizations for aquick data overview.

• Additionally, the system extracts the citation network data from theliterature.

• The citation network enables calculating how many times eachreference has been cite by a paper inside the analyzed dataset.

9

Services (cont.)

• NAILS also extracts and exports data about citation and authorcooperation networks that can be visualized (e.g. using Gephi).

• This dataset of citation connection can be used to calculate therelative influence of publications in the network.

10

How to Analyse

• NAILS works on publications available for download from ThomsonReuters Web of Science Core Collection.

• The user downloads the literature data from Web of Science anduploads it to NAILS via a web interface (HAMMER).

• The system then removes duplicate records and performs anexploratory data analysis on provided literature data.

11

Analysis Case Study

Case Study and Important Links

• A sample data retrieved from Web of Science with the search termof ”augmented reality education”.

• Important links:• https://webofknowledge.com/• http://nailsproject.net/• http://hammer.nailsproject.net/

12

https://webofknowledge.com/http://nailsproject.net/http://hammer.nailsproject.net/

Web of Science

Figure 2: Web of Science. 13

Core Collection

Figure 3: Web of Science core collection. 14

Search Results

Figure 4: Web of Science search results.

15

Save to Other File Formats

Figure 5: Save to other file formats.

16

Send to File

Figure 6: Send to file.

17

Zipped Content

Figure 7: Downloaded files and zipped contents.

18

Using HAMMER

Figure 8: HAMMER web interface.19

HAMMER (cont.)

Figure 9: HAMMER input.20

Analysis Processing

Figure 10: HAMMER analysis processing.

21

Analysis Results Page

Figure 11: HAMMER analysis results page.

22

Manual Installation

• Download R binaries: https://cran.r-project.org/• Download R Studio:

https://www.rstudio.com/products/rstudio/download/

• Download NAILS master package:https://github.com/aknutas/nails

23

https://cran.r-project.org/https://www.rstudio.com/products/rstudio/download/https://github.com/aknutas/nails

R Studio

Figure 12: R Studio.

24

Install Packages

• install.packages(”packagename”)• splitstackshape, reshape, plyr, stringr, tm, SnowballC, lda, LDAvis,

igraph, etc.

25

Set Directory

Figure 13: Set directory in R Studio.

26

Set Directory (cont.)

Figure 14: Set directory in R Studio (cont.).

27

Save Web of Science Results in Input

Figure 15: Store results from Web of Science to input folder in NAILS master.

28

Run Exploration

Figure 16: Open exploration.Rmd and click on Knit.

29

Case Study Output

NAILS and HAMMER Output

Figure 17: NAILS and HAMMER output.

30

CSV Files

• CSV stands for comma-separated values.• Files in the CSV format can be imported to and exported from

programs that store data in tables, such as Microsoft Excel.

31

CSV File Example

Figure 18: CSV file example from case study output.

32

CSV Files: How to open?

Figure 19: From Excel go to ’Data’ and select ’From Text’.

33

CSV Files: How to open? (cont.)

Figure 20: Select ’Delimited’ from the Text Import Wizard.

34

CSV Files: How to open? (cont.)

Figure 21: Select ’Semicolon’ from the Text Import Wizard.

35

CSV Files: How to open? (cont.)

Figure 22: Click on ’Finish’ from the Text Import Wizard.

36

CSV Files: How to open? (cont.)

Figure 23: Specify where you wish to place your data.

37

CSV Files: How to open? (cont.)

Figure 24: Output file,′literature by keywords.csv ′, opened.

38

Publication Year

Figure 25: Publication year.39

Relative Publication Volume

Figure 26: Relative publication volume. 40

Productive Authors

Figure 27: Productive authors.41

Most Cited Authors

Figure 28: Most cited authors. 42

Most Popular Publication

Figure 29: Most popular publications. 43

Most Cited Publication

Figure 30: Most cited publications.44

Popular Keywords

Figure 31: Popular keywords.45

Most Cited Keywords Keywords

Figure 32: Most cited keywords. 46

Important Papers

• In-degree in the citation network• Citation count provided by Web of Science• PageRank score in the citation network

47

No Included in the Dataset

Figure 33: Not included in the dataset.

48

Most Referenced Publication

Figure 34: Most referenced publications. 49

Topic Modeling Output

• Topic modeling is a type of statistical text mining method fordiscovering common topics that occur in a collection of documents.

• A topic modeling algorithm essentially looks through the abstractsincluded in the datasets for clusters of co-occurring of words and

groups them together by a process of similarity.

50

Topic Modeling Output (cont.)

Figure 35: Topic modeling.

51

Demonstration

Conclusion

Conclusion

• NAILS and HAMMER are valuable tools that can help you identifyrelevant keywords, authors, references, etc.

• The output can be used to expand your research to guarantee athorough literature review.

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IntroductionFunctionality and ServicesAnalysis Case StudyCase Study OutputDemonstrationConclusion