Publications and impact of the fields of management, economics, and sociology in Spain and France: Google scholar versus Scopus

Gantman, E.R., Dabós, M.P. 
Research output and impact of the fields of management, economics, and sociology in spain and france: An analysis using google scholar and scopus. Journal of the Association for Information Science and Technology. In press 
https://doi.org/10.1002/asi.24020

OBJECTIVES AND RESEARCH QUESTIONS

The goal of this article is therefore to explore the usefulness of Google Scholar for the study of the social sciences in non‐Anglophone countries, particularly analyzing the research output and impact by language.  In this regard, the research questions that we will address are the following: 

• What is the distribution of document types obtained from searching in Google Scholar? 
• Does the impact in terms of citations received in Google Scholar differ across different types of scientific documents? 
• How extended is the use of English in the social sciences in non‐Anglophone countries? 
• Does this use differ according to type of document? 
• Do scientific documents written in English have greater impact than those written in the vernacular language? 
• How do the results obtained from GS compare with those from Scopus?

METHODOLOGY

We address these issues with case studies of two non‐Anglophone countries, Spain and France, in three scientific fields, economics, management and sociology.
The total number of researchers selected for the study was 1,500 (each discipline has 250 individuals by country). We then collected the scientific output of the selected researchers from Google Scholar using the Publish or Perish 4.0 program.
The research output of the individual authors was assigned to one of the three disciplines according to their academic department of affiliation or to the main disciplinary topic of their research laboratory.
For each document from the researchers’ production supplied by the Publish or Perish software, we collected the following information:
1. Document type, which we classified into article, book, book chapter, PhD thesis, book review, congress presentation, or other (gray literature, working papers, etc.).
2. Publication year.
3. Publication language. In the case of Spain, we distinguished between Spanish or Castilian (the country's main language), dialect (category that includes the languages of some autonomous communities like Catalonia and the Basque country), English, and “others” as residual category. In the case of France, we distinguished between French, English, and “others” as residual category.
4. Number of citations received.
We also searched the production of the 1,500 researchers in Scopus, collecting similar data for each document entry.

RESULTS

The results suggest that, because of a documentary coverage in many languages that is greater than traditional bibliographic databases, GS is a very useful tool for examining the social sciences in non‐Anglophone countries. Compared with Scopus, Google Scholar finds more than 5 documents per document found in Scopus; but these differences in coverage vary by discipline.

Google Scholar dataset shows that the most utilized form for communication of scientific research is the article in the three disciplines and both countries, although books and book chapters also have a relevant share of total output. In addition, our findings show the importance of the vernacular languages. However, in the French case, the use of English appears to be very extended in economics. Moreover, we have also found that Scopus coverage of French documents in sociology is high (72% of total documents), which counters the existence of an English‐bias of this database in this particular case.

The level of internationalization of research output in the disciplines considered appears as variable, with sociology as the one most focused on the vernacular language of each country. This confirms the importance of local sociologies and, consequently, the possible fragmentation of this discipline in different local traditions. In contrast, economics is the most internationalized discipline.

Regarding the impact received by articles, books, and book chapters, there is a predominance of books in terms of received citations for the three disciplines and both countries in Google Scholar. Finally, and except for the case of articles in French sociology and for books in France, our results show that publishing in English has a great impact in the disciplines studied. This suggests that, in certain social sciences as well as in particular forms of diffusion of academic production, scholars may grant more attention to sources written in their country's vernacular language. Further research is needed in order to understand why this occurs and why it happens in certain countries and not in others.. 

The field of climate impact on societies in the past from Web of Science and Google Scholar

Susanne Mikki, Hemed Ali Al Ruwehy, Øyvind Liland Gjesdal, Marta Zygmuntowska
Filter bubbles in interdisciplinary research: a case study on climate and society
Library Hi Tech, 2018
https://doi.org/10.1108/LHT-03-2017-0052

INTRODUCTION
The purpose of this paper is to compare the content of Web of Science (WoS) and Google Scholar (GS) by searching the interdisciplinary field of climate and ancient societies. The authors aim at analyzing the retrieved documents by open availability, received citations, co-authors and type of publication

METHODOLOGY
The authors searched the services by a defined set of keyword. Data were retrieved and analyzed using a variety of bibliometric tools such as Publish or Perish, Sci2Tool and Gephi. In order to determine the proportion of open full texts based on the WoS result, the authors relocated the records in GS, using an off-campus internet connection.

RESULTS
The authors found that the top 1,000 downloadable and analyzable GS items matched poorly with the items retrieved by WoS. Based on this approach (subject searching), the services appeared complementary rather than similar. Even though the first search results differ considerably by service, almost each single WoS title could be located in GS. Based on GS’s full text recognition, the authors found 74 percent of WoS items openly available and the citation median of these was twice as high as for documents behind paywalls. 

Performance Behavior Patterns in Author-Level Metrics: A Disciplinary Comparison of Google Scholar Citations, ResearchGate, and ImpactStory

Enrique Orduña-Malea & Emilio Delgado López-Cózar
Performance Behavior Patterns in Author-Level Metrics: A Disciplinary Comparison of Google Scholar Citations, ResearchGate, and ImpactStory
Frontiers in Research Metrics and Analytics, 22 December 2017
https://doi.org/10.3389/frma.2017.00014 

INTRODUCTION
The main goal of this work is to verify the existence of diverse behavior patterns in academic production and impact, both among members of the same scientific community (inter-author variability) and for a single author (intra-author variability), as well as to find out whether this fact affects the correlation among author-level metrics (AutLMs) in disciplinary studies. in order to answer the main goal mentioned above, we pose the following research questions:
RQ1: Is it possible to detect different academic behavior patterns among authors working in the same discipline (inter-author variability) using the AutLMs available in online academic profile services?
RQ2: Is it possible to detect different academic behavior patterns by the same author (intra-author variability) using the AutLMs available in online academic profile services?
RQ3: If the two previous questions can be answered affirmatively, do these behaviors affect the correlations between AutLMs?

METHODOLOGY

Ttwo samples are examined: a general sample (members of a discipline, in this case Bibliometrics; n= 315 authors), and a specific sample (only one author; n = 119 publications). Four AutLMs (Total Citations, Recent Citations, Reads, and Online mentions) were extracted from three platforms (Google Scholar Citations, ResearchGate, and ImpactStory). 

RESULTS

The analysis of the general sample reveals the existence of different performance patterns, in the sense that there are groups of authors who perform prominently in some platforms, but exhibit a low impact in the others. The case study shows that the high performance in certain metrics and platforms is due to the coverage of document typologies, which is different in each platform (for example, Reads in working papers). 

The correlations (Spearman; α < 0.1) between the different metrics (Total Citations, Recent Citations, Reads, and Online mentions) 

As regards AutLMs, a non-linear distribution in the data extracted from the three platforms (Google Scholar Citations, ResearchGate, and ImpactStory) has been found. There are few authors with a high performance, and a long tail with moderate, low, or null performance. Moreover, the high performance authors are not the same across the three studied dimensions of impact (Citations, Reads, and Online mentions). The lack of correlation might be explained by the fact that each platform offers different documents, targeted to different audiences.

This fact has facilitated the identification of different patterns of online academic behavior in the studied platforms (RQ1). Some authors present a markedly formal performance (Citations, mainly to journal articles) while other authors stand out in Reads (both to articles and to other document typologies), or in Online mentions (mainly Articles). Combined patterns have also been found (high performance in Citations and Reads, and low in Online mentions). This issue evidences that the analysis of a single platform, not even considering of the demographic aspects related to the population of a discipline that is reflected, can mask the performance of an author who has particularly high or low values in any given platform.

Lastly, the ego-analysis has allowed us to confirm the existence of authors with different patterns of online academic behavior depending on the types of documents that they publish (RQ2). In this case, we could observe the existence of working papers with a high amount of Reads and Online mentions, as well as the existence of a large group of articles with a lower number of citations. That is, certain typologies are generating an impact (Reads in ResearchGate) that cannot be observed in other platforms. Again, the different nature of the research activity (article: generating knowledge; report: application of knowledge to solve a problem; educational materials: knowledge transfer, etc.) determines everything. The people who cite are scientists, the same ones that produce scientific knowledge, whereas practitioners read but do not cite as much, so it is less likely that they would cite other studies.

This fact again brings us to the need not only of considering different online academic profile platforms (in order to capture different impact profiles) but also to categorize the type of impact according to the document typologies, because a general analysis of authors might mask their actual impact.

All this makes us question the usefulness and precision of the correlation analyses of AutLMs within a discipline that have not taken into account inter-author or intra-author variability to model the multidimensional impact of authors. This is one of the aspects in which Altmetrics studies should focus their attention from now on.

Proceedings Scholar Metrics 2017: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2012-2016)

Emilio Delgado López-Cózar, Enrique Orduña-Malea, Proceedings Scholar Metrics 2017: H Index of proceedings on  Computer Science, Electrical & Electronic Engi
neering, and Communications according to Google Scholar Metrics (2012-2016). 
EC3 Reports, 22. Granada, 27th of December, 2017.. 

https://doi.org/10.13140/RG.2.2.11387.41768 

INTRODUCTION
PROCEEDINGS SCHOLAR METRICS is a ranking that displays proceedings (conferences, workshops, symposia, meetings) indexed in Google Scholar Metrics (GSM) on the areas of Computer Science, Electrical & Electronic Engineering, and Communications, which in this fourth edition corresponds to the period 2012-2016.

It is a well-known fact that conference proceedings play a major role as a means of scientific communication in all areas concerning Computer Engineering, Electronics, and Communications. The rapid rate at which knowledge is generated in these fields required the creation of a more dynamic system to communicate and publish research results. Conferences have historically fulfilled this role. 


The development of Google Scholar Metrics, launched on April 2012 with the goal of providing a ranking of scientific publications indexed on Google Scholar (journals, proceedings, repositories), provided that they had published at least 100 papers and received at least one citation in the last five years, has been a crucial step towards knowing the impact of conferences, which are so important in these areas.

Therefore, the system interface does not allow us to effectively determine which and how many conference proceedings GSM has indexed. In order to overcome this limitation, the objective of PROCEEDINGS SCHOLAR METRICS is to compile an inventory of all the conferences present in GSM concerning these fields of knowledge, and after that, rank them according to their scientific impact, as measured by the H index.

METHODOLOGY

Subject areas covered

Proceedings concerning Computer Science (theoretical, information theory, artificial intelligence, evolutionary computation, fuzzy systems, human computer interaction, computer vision & pattern recognition, computer hardware design, computing systems, signal processing, computer networks & wireless communication, robotics, automation & control theory, software systems, computer security & cryptography, computer graphics, databases & information systems, data mining & analysis, multimedia, bioinformatics & computational biology, biomedical technology, medical informatics, computational linguistics, education technology), Electrical & Electronic Engineering and Communications (telecommunications, remote sensing, antennas, radar, microware).

Search strategy

In order to identify the proceedings we followed two different strategies:

1. We collected all the conferences displayed in the subcategories concerning Computer Science, Electrical & Electronic Engineering, and Communications.
2. We collected the data about the conferences we had already found in previous editions of this report.
3. We carried out various searches using descriptive and pertinent keywords in order to locate the rest of relevant conferences. These searches took place on the second week of December, 2017.

The results of each search were downloaded (including the name of the conference, the h5-index, and the h5-median) and duplicates were removed. A manual check was carried out in order to filter out any irrelevant entries (journals, repositories, and conferences outside the scope of our study). A total of 1,918 conference proceedings were identified.

Criteria for the inclusion of Google Scholar Metrics proceedings

Proceedings that published at least 100 papers and received at least one citation in the last five years (2012-2016)

Sorting criteria and fields displayed

The proceedings are sorted by their H Index. In case of a tie, the discriminate value is the h5-median (the median number of citations for the articles that make up its h-index)

The information displayed for each conference is: H5-Index; H5-Median; Quartile 

This work is an update to the reports published in previous years:

Martín-Martín, A., Ayllón, J. M., Orduña-Malea, E., Delgado López-Cózar, E. (2016). Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2011-2015). EC3 reports 19. Granada, 13th of December, 2016, 
Available http://doi.org/10.13140/RG.2.2.16076.41605

Martín-Martín, A., Ayllón, J. M., Orduña-Malea, E., Delgado López-Cózar, E. (2015). Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2010-2014). EC3 reports 15. Granada, 14th of December, 2015. 
Available http://doi.org/10.13140/RG.2.1.4504.9681 

Martín-Martín, A.; Orduña-Malea, E.; Ayllón, J.M.; Delgado López-Cózar, E. Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2009-2013). EC3 Reports, 12.  Granada, 7th of January, 2015.

Available http://hdl.handle.net/10481/34148

MADAP: A method for depicting academic disciplines through Google Scholar Citations

Alberto Martín-Martín, Enrique Orduna-Malea, 

Emilio Delgado López-Cózar 

A novel method for depicting academic disciplines through Google Scholar Citations: 

The case of Bibliometrics

Scientometrics, in press. 

https://doi.org/10.1007/s11192-017-2587-4  

This article describes a procedure to generate a snapshot of the structure of a specific scientific community and their outputs based on the information available in Google Scholar Citations. We call this method MADAP (Multifaceted Analysis of Disciplines through Academic Profiles). 
The international community of researchers working in Bibliometrics, Scientometrics, Informetrics, Webometrics, and Altmetrics was selected as a case study. The records of the top 1,000 most cited documents by these authors were manually checked to fill any missing information and deduplicate fields like the journal names and book publishers. The results suggest that it is feasible to use Google Scholar Citations and the MADAP method to produce an accurate depiction of the community of researchers working in Bibliometrics (both specialist and occasional) and their publication habits (main publication venues such as journals and book publishers). 
Additionaly, the wide document coverage of Google Scholar (especially books and book chapters) enables more comprehensive analyses of the documents published in a specific discipline than were previously possible with other citation indexes, finally shedding light on what until now had been a blind spot in most citation analyses

Top 25 influential specialist/occasional authors in Bibliometrics according to Google Scholar Citations

Top 25 most influential documents in Bibliometrics according to Google Scholar Citations

 Top 25 most influential journals in Bibliometrics according to Google Scholar Citations

Network of the Bibliometrics discipline through the MADAP method in Google Scholar (author-journal)

Visibility in Google scholar of 48 Institutional Repositories of Peruvian Universities

Alhuay-Quispe, J., Quispe-Riveros, D., Bautista-Ynofuente, L., Pacheco-Mendoza, J. (2017). 

Metadata Quality and Academic Visibility Associated with Document Type Coverage in Institutional Repositories of Peruvian Universities. 

Journal of Web Librarianship, 1-14.

• https://doi.org/10.1080/19322909.2017.1382427 

This article analyzes level of metadata quality (MQ ratio) and level of academic visibility in Google Scholar (IGS ratio) associated with coverage of four types of documents (theses, articles, books, and conferences) in repositories of Peruvian universities. 
This research is a cross-sectional descriptive and correlational study with intentional non-probabilistic sampling that analyzes 48 repositories from national (n = 10) and private (n = 38) universities integrated in the Peruvian National Digital Repository Alicia (alicia.concytec.gob.pe). 
Regarding the MQ ratio, we found a median of 0.67 [RIC: 0.552–0.891] for national universities and a median of 0.65 [RIC: 0.407–0.838] for private universities (p = .542). Regarding the IGS ratio, we found a median of 0.32 [RIC: 0.241–0.596] for national universities and a median of 0.62 [RIC: 0.464–0.749] for private universities (p = .054). The p value in Spearman's rank correlation shows a moderate correlation (ρ = 0.594; p < .01) between MQ ratio and the thesis coverage indicator, and a low correlation (ρ = 0.157) between the index of document indexing in Google Scholar and the proportion of documents harvested in Alicia. 
We conclude that the highest proportion of academic visibility is concentrated in private universities, and the metadata quality number of items integrated in Alicia favors public universities.

Google Scholar as a source for scholarly evaluation: a bibliographic review of database errors

Enrique Orduna-Malea, Alberto Martín-Martín, 
Emilio Delgado López-Cózar
Google Scholar as a source for scholarly evaluation: a bibliographic review of database errors
Revista Española de Documentación Científica 40.4 (2017): e185.
http://dx.doi.org/10.3989/redc.2017.4.1500

The launch of Google Scholar back in 2004 meant a revolution not only in the scientific information search market but also in research evaluation processes. Its dynamism, unparalleled coverage, and uncontrolled indexing make Google Scholar an unusual product, especially when compared to traditional bibliographic databases. Conceived primarily as a discovery tool for academic information, it presents a number of limitations as a bibliometric tool.  The main objective of this chapter is to show how Google Scholar operates and how its core database may be used for bibliometric purposes. To do this, the general features of the search engine (in terms of document typologies, disciplines, and coverage) are analyzed. Lastly, several bibliometric tools based on Google Scholar data, both official (Google Scholar Metrics, Google Scholar Citations) and some developed by third parties (H Index Scholar, Publishers Scholar Metrics, Proceedings Scholar Metrics, Journal Scholar Metrics, Scholar Mirrors), as well as software to collect and process data from this source (Publish or Perish, Scholarometer), are introduced, aiming to illustrate the potential bibliometric uses of this source.

Google Scholar: The big data bibliographic tool

Delgado López-Cózar, E. Orduña-Malea, E.,  Martín-Martín, A.,  Ayllón, J.M. (2017). 
Google Scholar: The big data bibliographic tool. 
In: Cantu-Ortiz, FJ. (ed.). Research Analytics: Boosting University Productivity and Competitiveness through Scientometrics. 
CRC Press (Taylor & Francis Group), 2017 p. 59-80 
goo.gl/vvPf7g 

The launch of Google Scholar back in 2004 meant a revolution not only in the scientific

information search market but also in research evaluation processes. Its dynamism, unparalleled coverage, and uncontrolled indexing make Google Scholar an unusual product, especially when compared to traditional bibliographic databases. Conceived primarily as a discovery tool for academic information, it presents a number of limitations as a bibliometric tool.  The main objective of this chapter is to show how Google Scholar operates and how its core database may be used for bibliometric purposes. To do this, the general features of the search engine (in terms of document typologies, disciplines, and coverage) are analyzed. Lastly, several bibliometric tools based on Google Scholar data, both official (Google Scholar Metrics, Google Scholar Citations) and some developed by third parties (H Index Scholar, Publishers Scholar Metrics, Proceedings Scholar Metrics, Journal Scholar Metrics, Scholar Mirrors), as well as software to collect and process data from this source (Publish or Perish, Scholarometer), are introduced, aiming to illustrate the potential bibliometric uses of this source.

Global mapping of artificial intelligence in Google and Google Scholar

Omar M., Mehmood  A., Choi  G.S., Park, H.W. (2017).
Global mapping of artificial intelligence in Google and Google Scholar. 
Scientometrics, in press.
https://doi.org/10.1007/s11192-017-2534-4

The worldwide presence of AI needs to be quantified. This study proposes a descriptive approach and the use of multiple methods and data. An extensive electronic corpus of books was utilized to see the worldwide drift of intellectuals’ minds toward AI and identified related terms, their future trends, and convergence. 

Using the best bigram proposed by Ngrams Viewer, this study explores the human mind through Google query data, linking popular regions, countries, and related topics to the concept of AI. URL datasets were collected using two popular search engines (SEs), Google and Google Scholar (GS). A URL analysis identified key entities (organizations, institutes, and countries) and their yearly trends. 

Top-level domains revealed the global web ecology and the annual information growth of AI in SE environments. Information gathered through one approach was fed into the other, revealing a complementary relationship. AI is popular across the globe, and has left traces in many different countries. In this field, GS dominates Google, in relation to the number of sites and domains it includes. Top results reveal the popularity of AI among professionals, artists, programmers, and researchers. The pros and cons of the approaches are also discussed. 

In addition, this study aims to predict the impact of AI on society, as interpreted through the lenses of well-established theories. The dominance of AI may trap society into aspiring toward an easy life, dependent on intelligent machines. Consistent policies are needed to smooth out future economic cycles in the AI field.

Evolution of profiles of Consejo Superior de Investigaciones Científicas in Academia.edu, Google Scholar Citations and ResearchGate (2014-2015)

Ortega, JL (2017)
Toward a homogenization of academic social sites: A longitudinal study of profiles in Academia.edu, Google Scholar Citations and ResearchGate
Online Information Review, 41(6): 812-825
https://doi.org/10.1108/OIR-01-2016-0012 

Purpose

The purpose of this paper is to analyze the distribution of profiles from academic social networking sites according to disciplines, academic statuses and gender, and detect possible biases with regard to the real staff distribution. In this way, it intends to know whether these academic places tend to become specialized sites or, on the contrary, there is a homogenization process.

Design/methodology/approach

To this purpose, the evolution of profiles of one organization (Consejo Superior de Investigaciones Científicas) in three major academic social sites (Academia.edu, Google Scholar Citations and ResearchGate) through six quarterly samples since April 2014 to September 2015 are tracked.

Findings

Longitudinal results show important disciplinary biases but with strong increase of new profiles form different areas. They also suggest that these virtual spaces are gaining more stability and they tend toward a equilibrate environment.

Originality/value

This is the first longitudinal study of profiles from three major academic social networking sites and it allows to shed light on the future of these platforms’ populations.

The lost academic home: institutional affiliation links in Google Scholar Citations

Orduña-Malea, E., Ayllón, J. M., Martín-Martín, A., 
Delgado López-Cózar, E. (2017)
The lost academic home: institutional affiliation links in Google Scholar Citations. 
Online Information Review, 41 (6), 762-781
 https://doi.org/10.1108/OIR-10-2016-0302

.

Purpose

Google Scholar Citations (GSC) provides an institutional affiliation link which groups together authors who belong to the same institution. The purpose of this paper is to ascertain whether this feature is able to identify and normalize all the institutions entered by the authors, and whether it is able to assign all researchers to their own institution correctly.

Design/methodology/approach

Systematic queries to GSC’s internal search box were performed under two different forms (institution name and institutional e-mail web domain) in September 2015. The whole Spanish academic system (82 institutions) was used as a test. Additionally, specific searches to companies (Google) and world-class universities were performed to identify and classify potential errors in the functioning of the feature.

Findings

Although the affiliation tool works well for most institutions, it is unable to detect all existing institutions in the database, and it is not always able to create a unique standardized entry for each institution. Additionally, it also fails to group all the authors who belong to the same institution. A wide variety of errors have been identified and classified.

Research limitations/implications

Even though the analyzed sample is good enough to empirically answer the research questions initially proposed, a more comprehensive study should be performed to calibrate the real volume of the errors.

Practical implications

The discovered affiliation link errors prevent institutions from being able to access the profiles of all their respective authors using the institutions lists offered by GSC. Additionally, it introduces a shortcoming in the navigation features of Google Scholar which may impair web user experience.

Social implications

Some institutions (mainly universities) are under-represented in the affiliation feature provided by GSC. This fact might jeopardize the visibility of institutions as well as the use of this feature in bibliometric or webometric analyses.

Originality/value

This work proves inconsistencies in the affiliation feature provided by GSC. A whole national university system is systematically analyzed and several queries have been used to reveal errors in its functioning. The completeness of the errors identified and the empirical data examined are the most exhaustive to date regarding this topic. Finally, some recommendations about how to correctly fill in the affiliation data (both for authors and institutions) and how to improve this feature are provided as well.

Metric study of information literacy in latin america: from bibliometrics to altmetrics

Uribe-Tirado, A.; Alhuay-Quispe, J. (2017). 
Estudio métrico de ALFIN en Iberoamérica: de la bibliometría a las altmetrics. 
Revista Española de Documentación Científica,40(3): e180
doi:http://dx.doi.org/10.3989/redc.2017.3.1414

This study identifies the presence, productivity and influence of Ibero-American authors that write about information literacy (InfoLit). Using bibliometric and altmetric indicators, it seeks to analyze the impact and subsequent use of their scholarly works on social and scientific platforms. Fifty-five authors with the highest productivity were identified, based on the results of bibliometric studies on InfoLit carried out on both an international and Ibero-American scale in searches of major databases as well as publications collected in a Latin American wiki. 

Subsequently an analysis of bibliometric and altmetric indicators at the author and publication level was carried out, based on the results of searches on eight scientific platforms (Google Scholar, ResearchGate, Academia.edu, Mendeley, ORCID, IraLIS, E-LIS and EXIT), three social networks (Facebook, Twitter and LinkedIn), and data provided by a commercial supplier (Altmetric.com). 

Overall we found a greater presence of authors in ResearchGate (58%), Academia.edu (51%) and Google Scholar (49%) as opposed to Mendeley (25%) and ORCID (18%). Furthermore, as to social platforms, the greatest potential influence lies with Facebook, due to its high number of followers ( / top 10 authors). In addition, an analysis with the Spearman rho statistic, shows among some sources and platforms, a low correlation between the number of citations in Google Scholar and readings in Mendeley (r = 382) and low negative for mentions in blogs (r = 0,-237), Google+ (r = 0, -214) and Twitter (r = 0, -183). In conclusion, both the productivity and the impact-visibility center on specific authors writing about InfoLit, and various measurement resources show that for these authors there is a positive two-way impact from bibliometric to altmetric and vice versa

Comparing the number of citations of Google Scholar and Researchgate in a sample of Colombian researchers

Aguillo-Caño I., Uribe-Tirado A., López-López W. (2017)
Visibilidad de los investigadores colombianos según sus indicadores en Google Scholar y ResearchGate. Diferencias y similitudes con la clasificación oficial del sistema nacional de ciencia -COLCIENCIAS. 
Revista Interamericana de Bibliotecología, 40(3), 221-230. 
doi: 10.17533/udea.rib.v40n3a03

The aim of this study is to contextualize the results obtained regarding the classification of researchers who work in Colombian institutions according to their public Google Scholar - GSC citation profiles (1390 with an H index equal or higher than 5). 

To this end, the study compares its findings with the data obtained from the collection of Colombian authors on a social network named ResearchGate - RG and the local information provided by Colciencias, which is the Colombian agency that publishes researcher classification from a platform named ScienTI. 

Findings revealed significant discrepancies between GSC and RG findings regarding the four classification categories Colciencias provided. This suggests that Colciencias must reconsider its assessment criteria including new sources and indicators. Considering that the two sources (GSC, RG) and the (h index, RG-Index) indicators behave differently regarding disciplines, Colciencias must also be careful with disciplinary assignments adopting International classifications and developing discipline related indicators. Colombian academic and research organizations should become more active in recognizing the potential and importance of Internet platforms to visibilize their research work and increase its impact (Ciencia 2.0)

International Survey of Research University Faculty: Use of Bibliometric Ratings, Identifiers & Indicators

International Survey of Research University Faculty: Use of Bibliometric Ratings, Identifiers & Indicators
Report by Primary Research Group
ISBN No:978-157440-472-2

This study presents data from 325 faculty of major universities in the USA, Canada, the UK, Ireland and Australia about how they view bibliometric indicators such as the h-index, how trustworthy they are believed to be and how often they are checked or calculated.

CONTENTS

THE QUESTIONNAIRE 

INSTITUTIONAL AFFILIATIONS OF THE SURVEY PARTICIPANTS 

Characteristics of the Sample 

SUMMARY OF MAIN FINDINGS 

Personal Awareness of the h-index 

Frequency of Checking the H-Index 

Use of Journal Impact Factor Ratings and Rankings When Deciding on Publication Venue 

Ease of Finding Journal Impact Factors 

Views on Journal Impact Factor Trustworthiness 

Use Scholar Identifiers 

Use of Thomson Reuters Research ID [sic]

Use of Orchid ID 

Use of the International Standard Number Identifier 

Use of arXiv 

Use of Web of Science 

Use of Google Scholar 

Use of Scopus 

Use of JSTORE [sic]

Use of Journal Citation 

Use of Scimago, bepress and SciVal 

Use of SciFinder 

Use of CrossRef 

The study presents data on the use of particular tools and indicators, giving specific data for all of the following: Web of Science, Scopus, Google Scholar, ORCHID ID, Thomson-Reuters Research ID, Scimago, bepress, SciVal, JSTOR, International, SciFinder, arXiv and CrossRef, among others.

Data in the report is broken out by tenure status, gender, age, semester teaching load, academic field, academic title, and political views of the survey participant, as well as by the country or origin, public/private status and world ranking of the universities of the survey participants.

Just a few of this 113-page report’s many findings are that:

• Google Scholar was the most frequently used tool for bibliometrics, with 85% of the respondents reporting its use. All faculty age 30 or under reported using Google Scholar with this percentage declining to 77% of faculty 60 years and over.
• SciFinder use was reported by 7% of respondents, especially at private institutions (10%), by faculty 30 years or younger (22%), 
• 76% of faculty in the UK/Ireland had an ORCHID ID vs. only 35% in the USA.
• Political conservatives are more likely than those with more centrist or left-wing views to feel that bibliometric measures are trustworthy.
• Faculty in literature and languages found the most difficulty in finding journal impact factor data for use in their career planning