Twenty years of Wikipedia in scholarly publications: a bibliometric network analysis of the thematic and citation landscape | SpringerLink

Abstract:  Wikipedia has grown to be the biggest online encyclopedia in terms of comprehensiveness, reach and coverage. However, although different websites and social network platforms have received considerable academic attention, Wikipedia has largely gone unnoticed. In this study, we fill this research gap by investigating how Wikipedia is used in scholarly publications since its launch in 2001. More specifically, we review and analyze the intellectual structure of Wikipedia’s scholarly publications based on 3790 Web of Science core collection documents written by 10,636 authors from 100 countries over two decades (2001–2021). Results show that the most influential outlets publishing Wikipedia research include journals such as Plos one, Nucleic Acids Research, the Journal of the Association for Information Science and Technology, the Journal of the American Society for Information Science and Technology, IEEE Access, and Information Processing and Management. Results also show that the author collaboration network is very sparsely connected, indicating the absence of close collaboration among the authors in the field. Furthermore, results reveal that the Wikipedia research institutions’ collaboration network reflects a North–South divide as very limited cooperation occurs between developed and developing countries’ institutions. Finally, the multiple correspondence analysis applied to obtain the Wikipedia research conceptual map reveals the breadth, diversity, and intellectual thrust of the Wikipedia’s scholarly publications. Our analysis has far-reaching implications for aspiring researchers interested in Wikipedia research as we retrospectively trace the evolution in research output over the last two decades, establish linkages between the authors and articles, and reveal trending topics/hotspots within the broad theme of Wikipedia research.

 

An Exploration of Mendeley Reader and Google Scholar Citation for Analysing Indexed Article

Abstract— This paper aims to analyze the number of readers from the published articles of 100 Indonesian researchers in Mendeley reference management software. The list of Indonesian scientists is obtained from the webometrics ranking of scientists. We used the Application Programming Interface (API) of Mendeley to count the number of readers for each article in Mendeley and combine it with Google Scholar citation using the scrap method. We processed ten mostly cited articles that are indexed in the first page of the Google Scholar for each designated scientist. Furthermore, we used the Pearson method to analyze the correlation of the Mendeley readers count and the Google Scholar citation. The results show that they are correlated with a value of 0.266 according to the method of Pearson with N = 1000. Furthermore we found that many online Indonesian journals have no Digital Object Identifier (DOI) yet. Our evaluation of the publication results of 100 Indonesian researchers shows that authors who upload their scientific work on Mendeley, have higher citation number in Google Scholar, because their papers are widely available on the Internet.

Changes in the absolute numbers and proportions of open access articles from 2000 to 2021 based on the Web of Science Core Collection: a bibliometric study

Purpose:
The ultimate goal of current open access (OA) initiatives is for library services to use OA resources. This study aimed to assess the infrastructure for OA scholarly information services by tabulating the number and proportion of OA articles in a literature database.
Method:
We measured the absolute numbers and proportions of OA articles at different time points across various disciplines based on the Web of Science (WoS) database.
Results:
The number (proportion) of available OA articles between 2000 and 2021 in the WoS database was 12 million (32.4%). The number (proportion) of indexed OA articles in 1 year was 0.15 million (14.6%) in 2000 and 1.5 million (48.0%) in 2021. The proportion of OA by subject categories in the cumulative data was the highest in the multidisciplinary category (2000–2021, 79%; 2021, 89%), high in natural sciences (2000–2021, 21%–46%; 2021, 41%–62%) and health and medicine (2000–2021, 37%–40%; 2021, 52%–60%), and low in social sciences and others (2000–2021, 23%–32%; 2021, 36%–44%), engineering (2000–2021, 17%–33%; 2021, 31%–39%) and humanities and arts (2000–2021, 11%–22%; 2021, 28%–38%).
Conclusion:
Our study confirmed that increasingly many OA research papers have been published in the last 20 years, and the recent data show considerable promise for better services in the future. The proportions of OA articles differed among scholarly disciplines, and designing library services necessitates several considerations with regard to the customers’ demands, available OA resources, and strategic approaches to encourage the use of scholarly OA articles.

Escaping ‘bibliometric coloniality’, ‘epistemic inequality’

“Africa’s scholarly journals compete on an unequal playing field because of a lack of funding and the struggle to sustain academic credibility.

“These inequalities are exacerbated by the growing influence of the major citation indexes, leading to what we have called bibliometric coloniality,” say the authors of the book, Who Counts? Ghanaian academic publishing and global science, published by African Minds at the start of 2023.

“The rules of the game continue to be defined outside the continent. We hope that, in some small way, this book contributes to the renaissance and renewal of African-centred research and publishing infrastructures,” the authors say….”

CWTS :: Scientometrics Using Open Data

Open data sources such as Crossref, DataCite, ORCID, OpenAlex, OpenCitations, and many others offer important opportunities to perform scientometric analyses in more transparent, inclusive, and reproducible ways. The course Scientometrics Using Open Data in our CWTS course program provides an introduction to the use of these open data sources. The next edition of the course will take place online in October 2023. The course is offered jointly by CWTS and the Curtin Open Knowledge Initiative (COKI)….

Compared with proprietary scientometric data sources, open data sources enable more responsible approaches to the use of scientometric information in research assessment and research policy. The course Scientometrics Using Open Data aims to provide a practical introduction to open scientometric data sources and their use in research assessment and research policy contexts. The course focuses on the following topics:

The landscape of open data sources
Strengths and weaknesses of open data sources for different use cases
Accessing and using open data sources
Applications in research assessment and research policy
Future trajectories – deciding when open data sources will be the right choice for your use case…”

The role of open data in digital society: The analysis of scientific trending topics through a bibliometric approach

 

The analysis of contemporary society, characterized by technological, economic, political, social, and cultural changes, has become more challenging due to the development of the internet and information and communication technologies, which provide a vast and increasingly valuable source of information, knowledge, and data. Within this context, so-called open data—that is, data that are made public, especially by public administrations, through an open governance model (transparent and accessible to citizens) are assuming a significant role. This is a topic of growing importance that scientific research is addressing in an attempt to discern the multiplicity of social, educational, legal, technological, statistical, and methodological issues that underlie the creation and use of such data. This article aims to provide insights into understanding scientific trends on the topic of open data through a bibliometric approach. Specifically, a total of 3,110 publications related to the disciplinary fields of the social sciences and humanities published from 2013 to 2022 were collected. The data was then analyzed using network and factorial analysis techniques to detect the conceptual structure to identify the trends of topics and perspectives of research that characterize open data studies.

Are papers published in predatory journals worthless? A geopolitical dimension revealed by content-based analysis of citations | Quantitative Science Studies | MIT Press

This study uses content-based citation analysis to move beyond the simplified classification of predatory journals. We present that, when we analyze papers not only in terms of the quantity of their citations but also the content of these citations, we are able to show the various roles played by papers published in journals accused of being predatory. To accomplish this, we analyzed the content of 9,995 citances (i.e., citation sentences) from 6,706 papers indexed in the Web of Science Core Collection, which cites papers published in so-called “predatory” (or questionable) journals. The analysis revealed that the vast majority of such citances are neutral (97.3%), and negative citations of articles published in the analyzed journals are almost completely nonexistent (0.8%). Moreover, the analysis revealed that the most frequently mentioned countries in the citances are India, Pakistan, and Iran, with mentions of Western countries being rare. This highlights a geopolitical bias and shows the usefulness of looking at such journals as mislocated centers of scholarly communication. The analyzed journals provide regional data prevalent for mainstream scholarly discussions, and the idea of predatory publishing hides geopolitical inequalities in global scholarly publishing. Our findings also contribute to the further development of content-based citation analysis.

Investigating the dimensions of students’ privacy concern in the collection, use, and sharing of data for learning analytics

Abstract:  The datafication of learning has created vast amounts of digital data which may contribute to enhancing teaching and learning. While researchers have successfully used learning analytics, for instance, to improve student retention and learning design, the topic of privacy in learning analytics from students’ perspectives requires further investigation. Specifically, there are mixed results in the literature as to whether students are concerned about privacy in learning analytics. Understanding students’ privacy concern, or lack of privacy concern, can contribute to successful implementation of learning analytics applications in higher education institutions. This paper reports on a study carried out to understand whether students are concerned about the collection, use and sharing of their data for learning analytics, and what contributes to their perspectives. Students in a laboratory session (n = 111) were shown vignettes describing data use in a university and an e-commerce company. The aim was to determine students’ concern about their data being collected, used and shared with third parties, and whether their concern differed between the two contexts. Students’ general privacy concerns and behaviours were also examined and compared to their privacy concern specific to learning analytics. We found that students in the study were more comfortable with the collection, use and sharing of their data in the university context than in the e-commerce context. Furthermore, these students were more concerned about their data being shared with third parties in the e-commerce context than in the university context. Thus, the study findings contribute to deepening our understanding about what raises students’ privacy concern in the collection, use and sharing of their data for learning analytics. We discuss the implications of these findings for research on and the practice of ethical learning analytics

Just 35% Indian research papers open-access, BHU’s data analysis platform shows

“Only about 35% of India’s scientific research publications is open–access, even though a large chunk of the research itself is public-funded, an analysis of research data by a team at Banaras Hindu University (BHU) has found. It has also found that less than a third of Indian research papers have women as lead authors….

The analysis has produced interesting findings. For instance, researchers found that a sizable percent of research is not available as open access despite being funded by the government. According to its records, 35.13% of India’s research was open-access in 2019; out of the 20 countries considered, India was ahead of only China (34.45%) and Iran (32.49%)….”

Publication and data surveillance in academia | Research Information

“It is becoming increasingly clear that the core functions of higher education are destined to be quantified and that this data will be harvested, curated, and repackaged through a variety of enterprise management platforms. All aspects of the academic lifecycle, such as research production, publication, distribution, impact determination, citation analysis, grant award trends, graduate student research topic, and more can be sold, analysed, and gamed to an unhealthy degree. By unhealthy, we mean constricted and self-consuming as the output we develop is directly contingent on the input we receive. Well-meaning tools, such as algorithmically derived research suggestions and citation analysis, create a shrinking and inequitable academic landscape that favours invisibly defined metrics of impact that are reinforced through further citation thereby limiting the scope and scale of research available….

As the shift to open access gains momentum, there is danger of the unintended consequences as enterprise platforms seek to maximise profit as the models shift from under their feet. As Alexander Grossmann and Björn Brembs discuss, the cost creep incurred by libraries reflects this pivot shifting to a model of author costs, which are often supported by libraries, thereby adjusting costing methods from the backend subscription model to the front-end pay to publish model. It is not surprising or controversial that for-profit enterprise, database, and academic platform vendors are seeking to turn a profit. We should remain vigilant, however, to academia’s willingness to find the easy and convenient solution without considering the longer-term effects of what they are selling. In a recent industry platform webinar, academic enterprise representatives discussed the “alchemy” of user-derived data and their ability to repackage and sell this data, with consent, to development companies with their key take away being a driver towards increased revenue. More to the point, they had learned the lessons of the tech industry, and more specifically the social media companies in understanding the data we generate can be used to target us, to sell to us, to use us for further development. They discussed the ways in which the use of this data would become, like social media, intelligent and drive user behaviour – further cinching the knot on the closed-loop as algorithmically-based suggestions further constrain research and reinforce a status-quo enabled by profit motive in the guise of engagement, use, and reuse….”

Research assessment reform: From rhetoric to reality | Science|Business

“At the same time, there is a growing consensus – both in Europe and elsewhere in the world – that the current assessment system needs to be rethought for an age of open science, big data, digitalisation and the demand for cross-disciplinary methods and skills. There are calls to improve the use of metrics, better balance quantitative and qualitative factors, and broaden the scope of assessment to reflect the full diversity of inputs, outputs and practices in 21st century science. The ultimate goal? To move away from inappropriate use of journal- and publication-based metrics in research assessment, towards a combination of metrics and narratives that reflect the value of research outputs and (researchers’ activities) in a more nuanced way….”

Universities, rich in data, struggle to capture its value, study finds | UCLA

“Key takeaways

The nation’s colleges and universities produce a wealth of data from research, administrative operations and other sources.
A survey of higher ed administrators found that the institutions face major challenges in capturing that data and in making data from various sources work together.
The study’s authors contend that universities have been slower than organizations in other economic sectors to create senior-level positions focused on data quality, strategy, governance and privacy matters….”

Data blind: Universities lag in capturing and exploiting data | Science

Abstract:  Research universities are large, complex organizations that generate vast amounts of administrative and research data. If exploited effectively, these data can aid in addressing myriad challenges. Yet universities lag behind industry, business, and government in deriving strategic value from their data resources (1). We recently conducted interviews on the state of data-informed decision-making with university leaders who were highly attuned to how well their institutional data systems and organizational structures are serving them and to the kinds of data capture and exploitation most needed. Findings from this exploratory study shed light on ways in which universities are data rich, data poor, and—sometimes—intentionally data blind. They point toward the need for leadership that supports a panoramic view of the data infrastructure and policies at play within individual universities, whether realized by creating a new senior role with relevant authority and budget or through greater multistakeholder coordination.

 

Open Syllabus Analytics: A New Service from Open Syllabus

“This informational webinar will be used to introduce viewers to Open Syllabus Analytics. Open Syllabus Analytics (OSA) is a massive archive of the main activity of higher education: teaching. It provides top-down views of syllabi across thousands of schools to help faculty, staff, and publishers improve student outcomes. The service is flexible and effective across multiple use cases, including library collection development, tracking OER adoption, curriculum aid for teachers and graduate students, and more.”