لتحليل الدراسات السابقة Nails محاضرة برنامج د.شروق المقرن

1. NAILS Project
Network Analysis Interface for Literature Studies
Shiroq Al-Megren, PhD
King Saud University

2. Table of contents
1. Introduction
2. Functionality and Services
3. Analysis Case Study
4. Case Study Output
5. Demonstration
6. Conclusion
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3. Introduction

4. What is a literature review?
• A body of text that aims to review the critical points of current
knowledge on a particular topic.
• A comprehensive survey of publications in a specific field of study or
related to a particular line of research.
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5. 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.
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6. 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.
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7. 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 as
books or articles.”
• Social Network Analysis “Examining and investigating social
structures through network theory.”
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8. Social Network Analysis
Figure 1: Social Network Analysis for a literature search for ’social network
analysis’.
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9. NAILS
• NAILS is a tool for performing statistics and Social Network Analysis
(SNA) on citation data.
• Bibliometric Network Analysis “Statistical study of connections
between publications.”
• NAILS is a free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License.
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10. Functionality and Services

11. Serives
• NAILS works on publications available for download from Thomson
Reuters Web of Science Core Collection.
• It analyses seven essential variables for each publication, which
includes the authors, keywords, publication forum, article type, and
cited articles.
• The analysis identifies, for instance, the most cited articles and
authors, most common keywords, and journals with most
publications.
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12. Services (cont.)
• The analysis and statistics are accompanied with visualizations for a
quick data overview.
• Additionally, the system extracts the citation network data from the
literature.
• The citation network enables calculating how many times each
reference has been cite by a paper inside the analyzed dataset.
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13. Services (cont.)
• NAILS also extracts and exports data about citation and author
cooperation networks that can be visualized (e.g. using Gephi).
• This dataset of citation connection can be used to calculate the
relative influence of publications in the network.
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14. How to Analyse
• NAILS works on publications available for download from Thomson
Reuters Web of Science Core Collection.
• The user downloads the literature data from Web of Science and
uploads it to NAILS via a web interface (HAMMER).
• The system then removes duplicate records and performs an
exploratory data analysis on provided literature data.
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15. Analysis Case Study

16. Case Study and Important Links
• A sample data retrieved from Web of Science with the search term
of ”augmented reality education”.
• Important links:
• https://webofknowledge.com/
• http://nailsproject.net/
• http://hammer.nailsproject.net/
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17. Web of Science
Figure 2: Web of Science. 13

18. Core Collection
Figure 3: Web of Science core collection. 14

19. Search Results
Figure 4: Web of Science search results.
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20. Save to Other File Formats
Figure 5: Save to other file formats.
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21. Send to File
Figure 6: Send to file.
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22. Zipped Content
Figure 7: Downloaded files and zipped contents.
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23. Using HAMMER
Figure 8: HAMMER web interface.
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24. HAMMER (cont.)
Figure 9: HAMMER input.
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25. Analysis Processing
Figure 10: HAMMER analysis processing.
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26. Analysis Results Page
Figure 11: HAMMER analysis results page.
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27. 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
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28. R Studio
Figure 12: R Studio.
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29. Install Packages
• install.packages(”packagename”)
• splitstackshape, reshape, plyr, stringr, tm, SnowballC, lda, LDAvis,
igraph, etc.
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30. Set Directory
Figure 13: Set directory in R Studio.
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31. Set Directory (cont.)
Figure 14: Set directory in R Studio (cont.).
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32. Save Web of Science Results in Input
Figure 15: Store results from Web of Science to input folder in NAILS master.
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33. Run Exploration
Figure 16: Open exploration.Rmd and click on Knit.
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34. Case Study Output

35. NAILS and HAMMER Output
Figure 17: NAILS and HAMMER output.
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36. 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.
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37. CSV File Example
Figure 18: CSV file example from case study output.
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38. CSV Files: How to open?
Figure 19: From Excel go to ’Data’ and select ’From Text’.
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39. CSV Files: How to open? (cont.)
Figure 20: Select ’Delimited’ from the Text Import Wizard.
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40. CSV Files: How to open? (cont.)
Figure 21: Select ’Semicolon’ from the Text Import Wizard.
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41. CSV Files: How to open? (cont.)
Figure 22: Click on ’Finish’ from the Text Import Wizard.
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42. CSV Files: How to open? (cont.)
Figure 23: Specify where you wish to place your data.
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43. CSV Files: How to open? (cont.)
Figure 24: Output file, literature by keywords.csv , opened.
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44. Publication Year
Figure 25: Publication year.
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45. Relative Publication Volume
Figure 26: Relative publication volume. 40

46. Productive Authors
Figure 27: Productive authors.
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47. Most Cited Authors
Figure 28: Most cited authors. 42

48. Most Popular Publication
Figure 29: Most popular publications. 43

49. Most Cited Publication
Figure 30: Most cited publications.
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50. Popular Keywords
Figure 31: Popular keywords.
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51. Most Cited Keywords Keywords
Figure 32: Most cited keywords. 46

52. Important Papers
• In-degree in the citation network
• Citation count provided by Web of Science
• PageRank score in the citation network
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53. No Included in the Dataset
Figure 33: Not included in the dataset.
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54. Most Referenced Publication
Figure 34: Most referenced publications. 49

55. Topic Modeling Output
• Topic modeling is a type of statistical text mining method for
discovering common topics that occur in a collection of documents.
• A topic modeling algorithm essentially looks through the abstracts
included in the datasets for clusters of co-occurring of words and
groups them together by a process of similarity.
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56. Topic Modeling Output (cont.)
Figure 35: Topic modeling.
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57. Demonstration

58. Conclusion

59. Conclusion
• NAILS and HAMMER are valuable tools that can help you identify
relevant keywords, authors, references, etc.
• The output can be used to expand your research to guarantee a
thorough literature review.
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