Presentation at the European Scientometrics Summer School 2015 held in Leuven (Belgium) on July 17, 2015.

1. Google Scholar as a data source
for bibliometric analysis
Nicolás Robinson-Garcia

2. OBJECTIVES
GOOGLE SHOLAR AS A DATA SOURCE FOR
BIBLIOMETRIC ANALYSIS




3. AGENDA

4. Main characteristics of
Google Scholar

5. GS AS AN-INFORMATION DISCOVERY TOOL

6. GS AS AN-INFORMATION DISCOVERY TOOL

7. GS AS AN-INFORMATION DISCOVERY TOOL

8. GS AS AN-INFORMATION DISCOVERY TOOL

9. 


GS AS A TOOL FOR RESEARCHERS

10. 
GS AS A TOOL FOR RESEARCHERS

11. 

GS AS A TOOL FOR RESEARCHERS

12. 


GS AS A TOOL FOR RESEARCHERS

13. 



GS AS A TOOL FOR RESEARCHERS

14. •
ALERTS UPDATES
LIBRARY
+ CITE
GS AS A TOOL FOR RESEARCHERS

15. •
•
•
ALERTS
1 2
3

16. •
ALERTS
Following
Christian’s new
papers or
citations

17. •
•
–
–
–
–
–
•
UPDATES

18. UPDATES
Ok, I have published about
these topics, so I may be
interested on these papers
Ok, this paper cites me so it should
be related to my research

19. •
•
•
•
•
LIBRARY + CITE
•Cite easily from GS
results: formats 
MLA, APA, Chicago
•Get the formatted
reference and
copy/paste it into a
Bibliography.

20. •
•
LIBRARY + CITE

21. The Google Scholar family

22. •
PROFILES METRICS
SOURCE FOR
BIBLIOMETRIC ANALISYS
THE GOOGLE SCHOLAR FAMILY

23. •
•
•
PROFILES
Ranking of researchers
by keywords/areas are
generated through this
classification
TIP: there is always a field where you
can be the most cited author! 

24. •
•
•
•
•
–

PROFILES

28. CSIC RANKING OF RESEARCHERS ACCORDING TO GSC

29. UGRinvestiga – The time for bibliometric applications




30. UGRinvestiga – The time for bibliometric applications

31. 


UGRinvestiga – The time for bibliometric applications

32. • Easy to set up (just search for
your papers)
• Terrific tool for comparing
researchers within a field or
department
• Automatically updated basic
bibliometric data
• No restrictions on source,
language or area
• Everyone can measure their
performance (and their
colleagues')
PROFILES
• Data can be easily manipulated
(a researcher can self-claim
non-authored papers)
• Can stimulate vanity and ego
• Can generate unfair
comparisons (for example,
researchers from different
areas in a single univ)
• Can generate unfair analysis by
non-bibliometric experts
STRENGTHS WEAKNESSES

33. •
•
•
•
•
•
METRICS

36. • Free product to compare and rank
journals
• We can get impact information about
non-JCR journals and about national
and SSH publications
• Transparency: citations for every
paper that contributes to the h-index
can be checked
• High correlation with JCR Impact
factor (0.82)
• Simple to use and understand by any
scholar
• Can be easily replicated
• Methodological inconsistencies such
as comparing journals from
different areas
• Lack of proper bibliographic control
(duplicates, “dirty” data,…)
• No selection criteria
• No action against data manipulation
• No info about new updates (expected
to be updated yearly)
• Just top results are presented
• H index favours journals with high
production
STRENGTHS WEAKNESSES
METRICS

37. Google Scholar, a bibliometric
data source?

38. GETTING THE FACTS STRAIGHT




х
х
х
х

39. GETTING THE FACTS STRAIGHT

40. GETTING THE FACTS STRAIGHT

41. • 
•
JOURNALS
Cabezas & Delgado (2013)
Harzing & der Wal (2009)
GETTING THE FACTS STRAIGHT

42. GETTING THE FACTS STRAIGHT

43. •
•
•
GETTING THE FACTS STRAIGHT

44. SO, CAN I USE IT OR NOT?

45. SO, CAN I USE IT OR NOT?





46. HOW CAN I USE GS?

47. HOW CAN I USE GS?

48. SOME PRODUCTS BASED ON GS
Research Authors Publishers
Holistic
analysis model
Applied to Library & Information Sciences in Spain
http://www.biblioteconomia-documentacion-española.infoec3.es/

49. Conclusions

50. THE CRITICAL VIEW





51. 




THE OPTIMISTIC VIEW

52. 
 ‐ ‐ ‐
 ‐



FURTHER READINGS

53. Thank you!
elrobin@ugr.es wdb.ugr.es/~elrobin