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With the rise of alternate discovery services, such as Google Scholar, in conjunction with the increase in open access content, researchers have the option to bypass academic libraries when they search for and retrieve scholarly information. This state of affairs implies that academic libraries exist in competition with these alternate services and with the patrons who use them, and as a result, may be disintermediated from the scholarly information seeking and retrieval process. Drawing from decision and game theory, bounded rationality, information seeking theory, citation theory, and social computing theory, this study investigates how academic librarians are responding as competitors to changing scholarly information seeking and collecting practices. Bibliographic data was collected in 2010 from a systematic random sample of references on CiteULike.org and analyzed with three years of bibliometric data collected from Google Scholar. Findings suggest that although scholars may choose to bypass libraries when they seek scholarly information, academic libraries continue to provide a majority of scholarly documentation needs through open access and institutional repositories. Overall, the results indicate that academic librarians are playing the scholarly communication game competitively.

The purpose of this paper is to identify the utility of Web of Science, Scopus and Google Scholar as citation analysis tools for the social sciences.

The 25 most‐accessed articles in 163 social sciences journals are searched in three citation databases.

Web of Science has long been the only tool for citation analysis. Scopus and Google Scholar, while still new to the market, are complementary to Web of Science and in some cases can provide a more nuanced view of the importance of scholarly articles in the social sciences.

As libraries struggle to provide the best tools to their users, they may wish to consider the freely‐available Google Scholar as a substitute or complement to expensive databases such as Web of Science and Scopus.

Most analyses of citation databases have focused on the sciences. Because this study examined the social sciences literature, it has expanded on the research available on Web of Science, Google Scholar and Scopus.

The purpose of this study is to analyze the use of Google Scholar Citations’ profiling platform by library and information science (LIS) scholars in Pakistan.

Purposive sampling was used to collect Google Scholar Citations profiles between 15 November 2017 and 31 January 2018. Resultant data were analyzed in SPSS Version 21.

In terms of demographical data, the study results were consistent with previous studies of Pakistani LIS scholars. There were strong correlations between Google Scholar Citations metrics (publications, citations, h-index and i10-index). The results indicate that, compared with a 2011 survey of LIS academics in Pakistan, the overall uptake for this cohort remains relatively low. This cohort is not maximizing the opportunity provided by this specific online profiling system to increase research visibility.

As the study was limited to those Pakistani LIS scholars who already had a profile on ResearchGate, it would be useful to broaden the research to encompass all Pakistani LIS scholars.

The role of the librarian as an adviser in scholarly communication and impact can be extended to support scholars in the adoption of new online platforms for scholarly communication and visibility.

There have been no published research studies on Google Scholar Citations metrics in the context of Pakistani LIS scholars as a whole.

The study's main purpose is to scrutinize Google Scholar profiles and find the answer to the question, “Do authors play fair or manipulate Google Scholar Bibliometric Indicators like h-index and i10-index?”

The authors scrutinized the Google Scholar profiles of the top 50 library and science researchers claiming authorship of 21,022 publications. The bibliographic information of all the 21,022 publications like authorship and subject details were verified to identify accuracy, discrepancies and manipulation in their authorship claims. The actual and fabricated entries of all the authors along with their citations were recorded in the Microsoft Office Excel 2007 for further analyses and interpretation using simple arithmetic calculations.

The results show that the h-index of authors obtained from the Google Scholar should not be approved at its face value as the variations exist in the publication count and citations, which ultimately affect their h-index and i10 index. The results reveal that the majority of the authors have variations in publication count (58%), citations (58%), h-index (42%) and i10-index (54%). The magnitude of variation in the number of publications, citations, h-index and i10-index is very high, especially for the top-ranked authors.

The scope of the study is strictly restricted to the faculty members of library and information science and cannot be generalized across disciplines. Further, the scope of the study is limited to Google Scholar and caution needs to be taken to extend results to other databases like Web of Science and Scopus.

The study has practical implications for authors, publishers, and academic institutions. Authors must stop the unethical research practices; publishers must adopt techniques to overcome the problem and academic institutions need to take precautions before hiring, recruiting, promoting and allocating resources to the candidates on the face value of the Google Scholar h-index. Besides, Google needs to work on the weak areas of Google Scholar to improve its efficacy.

The study brings to light the new ways of manipulating bibliometric indicators like h-index, and i10-index provided by Google Scholar using false authorship claims.

The purpose of this study was to discover growing, stable and declining knowledge management (KM) research trends.

Citations to 100 KM citation classics as identified by Serenko and Dumay (2015) were collected and analyzed for growing, stable and declining research trends.

This research has two findings that were not theoretically expected. First, a majority of KM citation classics exhibit a bimodal citation distribution peak. Second, there are a growing number of citations for all research topics. These unexpected findings warranted further theoretical elaboration and empirical investigation. The analysis of erroneous citations and a five-year citation trend (2009 – 2013) reveals that the continuously growing volume of citations may result from what the authors call the Google Scholar Effect.

The results from this study open up two significant research opportunities. First, more research is needed to understand the impact Google Scholar is having on domains beyond KM. Second, more comprehensive research on the impact of erroneous citations is required because these have the most potential for damaging academic discourse and reputation.

Researchers need to be aware of how technology is changing their profession and their citation behavior because of the pressure from the contemporary “publish or perish” environment, which prevents research from being state-of-the-art. Similarly, KM reviewers and editors need to be more aware of the pressure and prevalence of mis-citations and take action to raise awareness and to prevent mis-citations.

This study is important from a scientometric research perspective as part of a growing research field using Google Scholar to measure the impact and power it has in influencing what gets cited and by whom.

Seven years after the release of Google Scholar in 2004, it was enhanced by a new module, the Google Scholar Author Citation Tracker (GSACT), currently a small subset of the complete Google Scholar (GS) database. The aim of this paper is to focus on this enhancement.

The paper discusses the Google Scholar Author Citation Tracker, its features, potential benefits and problems.

GSACT allows registered users to create and edit their scientific profiles and some bibliometric indicators, such as the h‐index, total citation counts, and the i10 index. These metrics are provided for the entire academic career of authors and for the most recent five‐year period. The new module also offers some long overdue essential options, such as sorting result lists of the documents by their publication year, title, and the citations received

The paper shows that, at present, GSACT may be too little, too late. However, with an extension of the current clean‐up project it could possibly become a really scholarly resource in the long run.

The purpose of this paper is to discuss the new scientific search service Google Scholar (GS). It aims to discuss this search engine, which is intended exclusively for searching scholarly documents, and then empirically test its most important functionality. The focus is on an exploratory study which investigates the coverage of scientific serials in GS.

The study is based on queries against different journal lists: international scientific journals from Thomson Scientific (SCI, SSCI, AH), open access journals from the DOAJ list and journals from the German social sciences literature database SOLIS as well as the analysis of result data from GS. All data gathering took place in August 2006.

The study shows deficiencies in the coverage and up‐to‐dateness of the GS index. Furthermore, the study points out which web servers are the most important data providers for this search service and which information sources are highly represented. The paper can show that there is a relatively large gap in Google Scholar's coverage of German literature as well as weaknesses in the accessibility of Open Access content. Major commercial academic publishers are currently the main data providers.

Five different journal lists were analysed, including approximately 9,500 single titles. The lists are from different fields and of various sizes. This limits comparability. There were also some problems matching the journal titles of the original lists to the journal title data provided by Google Scholar. The study was only able to analyse the top 100 Google Scholar hits per journal.

The paper concludes that Google Scholar has some interesting pros (such as citation analysis and free materials) but the service cannot be seen as a substitute for the use of special abstracting and indexing databases and library catalogues due to various weaknesses (such as transparency, coverage and up‐to‐dateness).

The authors do not know of any other study using such a brute force approach and such a large empirical basis. The study can be considered as using brute force in the sense that it gathered lots of data from Google and then analysed the data in a macroscopic way.

The purpose of this paper is to is to discuss the results of recent experiments in calculating the h‐index and other bibliometric and scientometric indicators from Google Scholar with the Publish or Perish software.

The paper discusses the Publish or Perish (PoP) software and finds that is a swift and elegant tool to provide the essential output features that Google Scholar does not offer.

It is found that PoP allows the user to edit the result lists presented in a compact, efficient grid‐format. It facilitates the identification and removal of duplicate entries by offering dynamic sorting of the set by eight metadata elements, un‐checking items and instant recalculation of the indicators.

Some changes are recommended to enhance this useful utility by allowing users to clean and edit the erroneous entries in the result set, and then back‐load it to PoP for the recalculation of the indicators. It is also suggested that the option to upload into PoP the result lists produced in CSV format from Web of Science and Scopus (which have much more reliable and reproducible data than Google Scholar) should also be offered.

Potential ethnocentric biases in stated preference journal rankings are reviewed and revealed preference ranking methods are investigated. The aim of the paper is to identify an approach to ranking journals that minimises ethnocentric biases and better represents the international impact of research.

Coverage of marketing journals in Ulrich's, EBSCO, SSCI, JCR, Scopus and Google Scholar is explored. Citing references to 20 articles are analysed to determine citation time lags and explore the content of SSCI, Scopus and Google Scholar. To further review the extent of citation coverage, h‐index scores are generated for ten marketing journals using data from SSCI, Scopus and Google Scholar. In total, 36 marketing journals are ranked using the g‐index and Google Scholar data and results are compared to ten published rankings.

Stated preference ranking studies of marketing journals rely on US‐based respondents. The coverage of EBSCO, SSCI, JCR and Scopus databases is not representative of marketing's literature as they have few international sources, and a disproportionate coverage of US‐based journals. Google Scholar provides broader international coverage. The Impact Factor may be inappropriate for marketing journals as a large proportion of citations occur more than five years post‐publication. Results indicate that the g‐index is a superior approach to measuring the impact of marketing journals internationally.

Exposure of the limitations in existing ranking methods should encourage improvements in the development and use of journal rankings.

The investigations present original evidence to support long‐term concerns about approaches to journal ranking and citation analysis.

The purpose of this paper is to investigate the usage, captures, mentions, social media and citations of highly cited papers of Library and information science (LIS).

This study is quantitative research that was conducted using scientometrics and altmetrics indicators. The research sample consists of LIS classic papers. The papers contain highly cited papers of LIS that are introduced by Google Scholar. The research data have been gathered from Google Scholar, Scopus and Plum Analytics Categories. The data analysis has been done by Excel and SPSS applications.

The data indicate that among the highly cited articles of LIS, the highest score regarding the usage, captures, mentions and social media and the most abundance of citations belong to “Citation advantage of open access articles” and “Usage patterns of collaborative tagging systems.” Based on the results of Spearman statistical tests, there is a positive significant correlation between Google Scholar Citations and all studied indicators. However, only the correlation between Google Scholar Citations with capture metrics (p-value = 0.047) and citation metrics (p-value = 0.0001) was statistically significant.

Altmetrics indicators can be used as complement traditional indicators of Scientometrics to study the impact of papers. Therefore, the Altmetrics knowledge of LIS researchers and experts and practicing new studies in this field will be very important.