Poster presented at #STI2014 in Leiden, The Netherlands - http://sti2014.cwts.nl/Home

1. Extracting and sharing data citations from Google Scholar for collaborative exploitation
Sibele Fausto*, Tiago Rodrigo Marçal Murakami**
There are studies that have drawn attention to the lack of indexing for the titles of scien-tific
journals in the Social Sciences, Applied Social Sciences and Humanities in large com-mercial
databases (Frandsen & Nicolaisen, 2008; Neuhaus & Daniel, 2007). This lack is
even more acute when it comes to journals concerned with these areas published in lan-guages
other than English and published in developing countries (Archambault & Lari-vière,
2010), which makes it difficult to carry out an investigation of the importance and
impact of these journals.
This situation is changing as a result of the new opportunities provided by the emergence
of Open Access (OA) and tools as the search engine Google Scholar (GS) and software for
data processing such as Publish or Perish - PoP (Harzing, 2007). The increasing shift of So-cial
Sciences and Humanities journals to the Web - including those of Library and Infor-mation
Science (LIS) is making them more widespread. This is allowing detailed searches
to be conducted through GS and the recovery of citations of articles, which can be regard-ed
as an alternative to traditional databases in bibliometrics studies on the impact of sci-entific
production published in these areas. In addition it highlights the fact that GS is a
free access source, in contrast with expensive commercial databases. It has a broad cover-age
of other kinds of material, even in the Social Sciences and Humanities (SSH), such as
books, book chapters, conference materials, etc. which are not normally covered by tradi-tional
databases and hence it is able to make a comprehensive recovery of open access
journals, in languages other than English, some of which come from emerging countries.
However, this apparently favorable context for research into bibliometrics in these areas
still faces challenges owing to questions about the reliability of the GS as a data source
(Jacsó, 2010). This criticism regarding to GS is a restatement of the need for more re-search
into the tool to finds a rational basis for understanding the full potential of Google
Scholar for bibliometrics studies, especially in areas not covered by commercial databases
(Caregnato, 2011).
This situation stimulated our attempt to share citation data from Brazilian LIS journals as a
pilot scheme to allow further investigation by the Brazilian scientometrics community in
employing Google Scholar with the aim of encouraging its greater use for bibliometric
purposes.
This pilot scheme adopted the following procedures:
a. Conducting a survey of LIS journals titles through
compiling lists of those that exist on the web;
b. Carrying out searches using PoP software for Win-dows,
with the journal title as a parameter, and con-firming
the official titles and abbreviations, in the
period from January 28, 2014 to March 02, 2014;
c. Displaying the results in Google Drive spread-sheets,
one for each retrieved journal title;
d. Creating a spreadsheet that brings together all
the spreadsheets with the articles that had at least
one citation;
e. Carrying out statistical tests using Excel and Tab-leau
Public.
Google Drive allows its contents to be shared publicly,
and the extracted data to be
made available through the fol-lowing
link:
https://docs.google.com/
spreadsheets/
d/19kcMMnfi_5Ohe60_mev-myFc85FkppqRJy-
HhXpfB_Q/
edit.
Data extraction from the GS with PoP resulted in a total of 24 Brazilian LIS jour-nals,
all in open access. However, the searches recovered some inaccurate data
which were then analyzed article by article and those with inconsistencies were
withdrawn. The data obtained allowed some exploratory exercises to be conduct-ed
with Tableau Public, by various categorizations
such as the received citations for each journal, in-cluding
citations per year and the articles cited,
among others. These preliminary exercises were also
publicly shared through the following link:
http://public.tableausoftware.com/views/
EstudodascitaesrecebidasporperidicosdaCI/
Citaesrecebidasporperidi-cos?:
embed=y&:display_count=no, e.g. as shown in
Figure 1.
Figure 1. Number of Citations per journal and per year
Citation studies are an important subject research in Bibliometrics and their
sources of reliable data were, until recently, a prerogative of restrictive and ex-pensive
commercial databases, despite these sources still continue to show in-consistencies
as is widely discussed in the literature. Google Scholar provides an
alternative source to these studies, particularly in the areas of the SSH, where
many journals are not considered by the large databases.
The emergence of tools that facilitate the extraction and data processing from
GS, such as PoP and tools like Google Refine, Google Drive and Tableau Public
help to simplify the task of validating these data. In our view, the public sharing
of pretreated citation data can stimulate more collaborative investigations by the
community of Brazilian scientometricians with the aim to demonstrate the ca-pacity
of Google Scholar to act as an alternative and reliable data source in the
metrical studies of national journals and thus enable better measures of the SSH
results in the context of scientific evaluation in Brazil.
References
Archambault, E. & Larivière, V. The limits of bibliometrics for the analysis of the social sciences and humanities literature (2010). In UNESCO (Ed.), 2010 World Social Science Report: Knowledge Divides (pp. 251-254). Paris: UNESCO,
International Social Science Council. Retrieved February 20, 2014 from: http://unesdoc.unesco.org/images/0018/001883/188333e.pdf.
Caregnato, S. E. (2011). Google Acadêmico como ferramenta para os estudos de citações: avaliação da precisão das buscas por autor. Ponto de Acesso, 5 (3), 72-86.
Frandsen, T.F. & Nicolaisen, J. (2008). Intradisciplinary differences in database coverage and the consequences for bibliometric research. Journal of the American Society for Information Science and Technology, 59 (10), 1570-1581.
Harzing, A.-W. Publish or Perish (2007). Retrieved February 20, 2014 from: http://www.harzing.com/pop.htm.
JACSÓ, P. (2010). Metadata mega mess in Google Scholar. Online Information Review, 34 (1), 175–191.
Neuhaus, C.; Daniel, H-D. (2007). Data sources for performing citation analysis: An overview. Journal of Documentation, 64 (2), 193-210.
Background and purpose
Methods
Preliminary findings
Final considerations
*sifausto@usp.br
Escola de Comunicações e Artes, University of São Paulo,
Av. Prof. Lúcio M. Rodrigues, 443, São Paulo, SP, CEP 05608-020 (Brazil)
**tiago.murakami@dt.sibi.usp.br
Departamento Técnico, Sistema Integrado de Bibliotecas, University of São Paulo
Rua da Biblioteca, S/N, Complexo Brasiliana, Piso Embasamento, São Paulo, SP, CEP 05508-050 (Brazil)