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In the humanities and social sciences, bibliometric methods for the assessment of research performance are (so far) less common. This study uses a concrete example in an attempt to evaluate a research institute from the area of social sciences and humanities with the help of data from Google Scholar ( GS). In order to use GS for a bibliometric study, we developed procedures for the normalization of citation impact, building on the procedures of classical bibliometrics. In order to test the convergent validity of the normalized citation impact scores, we calculated normalized scores for a subset of the publications based on data from the Web of Science ( WoS) and Scopus. Even if scores calculated with the help of GS and the WoS/ Scopus are not identical for the different publication types (considered here), they are so similar that they result in the same assessment of the institute investigated in this study: For example, the institute's papers whose journals are covered in the WoS are cited at about an average rate (compared with the other papers in the journals). [ABSTRACT FROM AUTHOR]

This study presents and explains the phenomenon of indexjacking, which involves the systematic infiltration of hijacked journals into international indexing databases, with Scopus being one of the most infiltrated among these databases. Through an analysis of known lists of hijacked journals, the study identified at least 67 hijacked journals that have penetrated Scopus since 2013. Of these, 33 journals indexed unauthorized content in Scopus and 23 compromised the homepage link in the journal's profile, while 11 did both. As of September 2023, 41 hijacked journals are still compromising the data of legitimate journals in Scopus. The presence of hijacked journals in Scopus is a challenge for scientific integrity due to the legitimization of unreliable papers that have not undergone peer review and compromises the quality of the Scopus database. The presence of hijacked journals in Scopus has far‐reaching effects. Papers published in these journals may be cited, and unauthorized content from these journals in Scopus is thus imported into other databases, including ORCID and the WHO COVID‐19 Research Database. This poses a particular challenge for research evaluation in those countries, where cloned versions of approved journals may be used to acquire publications and verifying their authenticity can be difficult. [ABSTRACT FROM AUTHOR]

The paper reports a longitudinal analysis of the topical and methodological development of Library and Information Science (LIS). Its focus is on the effects of researchers' disciplines on these developments. The study extends an earlier cross‐sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706–1722) by a coordinated dataset representing a content analysis of articles published in 31 scholarly LIS journals in 1995, 2005, and 2015. It is novel in its coverage of authors' disciplines, topical and methodological aspects in a coordinated dataset spanning two decades thus allowing trend analysis. The findings include a shrinking trend in the share of LIS from 67 to 36% while Computer Science, and Business and Economics increase their share from 9 and 6% to 21 and 16%, respectively. The earlier cross‐sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706–1722) for the year 2015 identified three topical clusters of LIS research, focusing on topical subfields, methodologies, and contributing disciplines. Correspondence analysis confirms their existence already in 1995 and traces their development through the decades. The contributing disciplines infuse their concepts, research questions, and approaches to LIS and may also subsume vital parts of LIS in their own structures of knowledge production. [ABSTRACT FROM AUTHOR]

Interdisciplinary research is widely recognized as necessary to tackle some of the grand challenges facing humanity. It is generally believed that interdisciplinarity is becoming increasingly prevalent among Science, Technology, Engineering, and Mathematics (STEM) fields. However, little is known about the evolution of interdisciplinarity in the Social Sciences. Also, how interdisciplinarity and its various aspects evolve over time has seldom been closely quantified and delineated. This paper answers these questions by capturing the disciplinary diversity of the knowledge base of scientific publications in nine broad Social Sciences fields over 55 years. The analysis considers diversity as a whole and its three distinct aspects, namely variety, balance, and disparity. Ordinary least squares (OLS) regressions are also conducted to investigate whether such change, if any, can be found among research with similar characteristics. We find that learning widely and digging deeply have become one of the norms among researchers in Social Sciences. Fields acting as knowledge exporters or independent domains maintain a relatively stable homogeneity in their knowledge base while the knowledge base of importer disciplines evolves towards greater heterogeneity. However, the increase of interdisciplinarity is substantially smaller when controlling for several author and publication related variables. [ABSTRACT FROM AUTHOR]

We present a search system for grammatically analyzed corpora of Finnish parliamentary records and interviews with former parliamentarians, annotated with metadata of talk structure and involved parliamentarians, and discuss their use through carefully chosen digital humanities case studies. We first introduce the construction, contents, and principles of use of the corpora. Then we discuss the application of the search system and the corpora to study how politicians talk about power, how ideological terms are used in political speech, and how to identify narratives in the data. All case studies stem from questions in the humanities and the social sciences, but rely on the grammatically parsed corpora in both identifying and quantifying passages of interest. Finally, the paper discusses the role of natural language processing methods for questions in the (digital) humanities. It makes the claim that a digital humanities inquiry of parliamentary speech and interviews with politicians cannot only rely on computational humanities modeling, but needs to accommodate a range of perspectives starting with simple searches, quantitative exploration, and ending with modeling. Furthermore, the digital humanities need a more thorough discussion about how the utilization of tools from information science and technologies alter the research questions posed in the humanities. [ABSTRACT FROM AUTHOR]

Contributing to the literature on knowledge infrastructure maintenance, this article describes a historical longitudinal analysis of revenue streams employed by four social science data organizations: the Roper Center for Public Opinion, the Inter‐university Consortium for Political and Social Research (ICPSR), the UK Data Archive (UKDA), and the LIS Cross‐National Data Center in Luxembourg (LIS). Drawing on archival documentation and interviews, we describe founders' assumptions about revenue, changes to revenue streams over the long term, practices for developing and maintaining revenue streams, the importance of financial support from host organizations, and how the context of each data organization shaped revenue possibilities. We extend conversations about knowledge infrastructure revenue streams by showing the types of change that have occurred over time and how it occurs. We provide examples of the types of flexibility needed for data organizations to remain sustainable over 40–60 years of revenue changes. We distinguish between Type A flexibilities, or development of new products and services, and Type B flexibilities, or continuous smaller adjustments to existing revenue streams. We argue that Type B flexibilities are as important as Type A, although they are easily overlooked. Our results are relevant to knowledge infrastructure managers and stakeholders facing similar revenue challenges. [ABSTRACT FROM AUTHOR]

Websites offer an unobtrusive data source for developing and analyzing information about various types of social science phenomena. In this paper, we provide a methodological resource for social scientists looking to expand their toolkit using unstructured web-based text, and in particular, with the Wayback Machine, to access historical website data. After providing a literature review of existing research that uses the Wayback Machine, we put forward a step-by-step description of how the analyst can design a research project using archived websites. We draw on the example of a project that analyzes indicators of innovation activities and strategies in 300 U.S. small- and medium-sized enterprises in green goods industries. We present six steps to access historical Wayback website data: (a) sampling, (b) organizing and defining the boundaries of the web crawl, (c) crawling, (d) website variable operationalization, (e) integration with other data sources, and (f) analysis. Although our examples draw on specific types of firms in green goods industries, the method can be generalized to other areas of research. In discussing the limitations and benefits of using the Wayback Machine, we note that both machine and human effort are essential to developing a high-quality data set from archived web information. [ABSTRACT FROM AUTHOR]

A 5‐year project to study scientific data uses in geography, starting in 1999, evolved into 20 years of research on data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. By emulating the "team science" approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. Building upon Paul N. Edwards's model of "making global data"—collecting signals via consistent methods, technologies, and policies—to "make data global"—comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. We reflect on continuity over generations of students and staff, transitions between grants, transfer of legacy data between software tools, research methods, and the role of professional data managers in the social sciences. [ABSTRACT FROM AUTHOR]

This study is concerned with differences in referencing patterns between book literature and periodical publications. Four indicators, the mean reference rate per page, the percentage of references to Web of Science journal literature, the mean reference age, and Price Index, were applied to analyze the reference patterns of three publication types: books, book chapter articles and journal articles. References of publications indexed in Web of Science Core Collection were analyzed for two periods (2005‐2009, 2010‐2013) and across 15 disciplines. Journal article authors cite more recent references and more references from serial publications than monograph authors. The difference between the sciences and the SSH is as obvious as the difference between periodical and non‐serial publications. However, the reference patterns of social sciences are much more similar to science fields than humanities, especially for monographs. The subject characteristics of reference pattern are strongly affected by publication types. Furthermore, journal publications have stronger associations between ageing indicators and the share of WoS journal references than monographs. [ABSTRACT FROM AUTHOR]

The study analyses contributions to Library and Information Science (LIS) by researchers representing various disciplines. How are such contributions associated with the choice of research topics and methodology? The study employs a quantitative content analysis of articles published in 31 scholarly LIS journals in 2015. Each article is seen as a contribution to LIS by the authors' disciplines, which are inferred from their affiliations. The unit of analysis is the article‐discipline pair. Of the contribution instances, the share of LIS is one third. Computer Science contributes one fifth and Business and Economics one sixth. The latter disciplines dominate the contributions in information retrieval, information seeking, and scientific communication indicating strong influences in LIS. Correspondence analysis reveals three clusters of research, one focusing on traditional LIS with contributions from LIS and Humanities and survey‐type research; another on information retrieval with contributions from Computer Science and experimental research; and the third on scientific communication with contributions from Natural Sciences and Medicine and citation analytic research. The strong differentiation of scholarly contributions in LIS hints to the fragmentation of LIS as a discipline. [ABSTRACT FROM AUTHOR]

The emergence of large multi‐institutional digital libraries has opened the door to aggregate‐level examinations of the published word. Such large‐scale analysis offers a new way to pursue traditional problems in the humanities and social sciences, using digital methods to ask routine questions of large corpora. However, inquiry into multiple centuries of books is constrained by the burdens of scale, where statistical inference is technically complex and limited by hurdles to access and flexibility. This work examines the role that exploratory data analysis and visualization tools may play in understanding large bibliographic datasets. We present one such tool, HathiTrust+Bookworm, which allows multifaceted exploration of the multimillion work HathiTrust Digital Library, and center it in the broader space of scholarly tools for exploratory data analysis. [ABSTRACT FROM AUTHOR]

The amount of annually published scholarly articles is growing steadily, as is the number of indicators through which impact of publications is measured. Little is known about how the increasing variety of available metrics affects researchers' processes of selecting literature to read. We conducted ranking experiments embedded into an online survey with 247 participating researchers, most from social sciences. Participants completed series of tasks in which they were asked to rank fictitious publications regarding their expected relevance, based on their scores regarding six prototypical metrics. Through applying logistic regression, cluster analysis, and manual coding of survey answers, we obtained detailed data on how prominent metrics for research impact influence our participants in decisions about which scientific articles to read. Survey answers revealed a combination of qualitative and quantitative characteristics that researchers consult when selecting literature, while regression analysis showed that among quantitative metrics, citation counts tend to be of highest concern, followed by Journal Impact Factors. Our results suggest a comparatively favorable view of many researchers on bibliometrics and widespread skepticism toward altmetrics. The findings underline the importance of equipping researchers with solid knowledge about specific metrics' limitations, as they seem to play significant roles in researchers' everyday relevance assessments. [ABSTRACT FROM AUTHOR]

Recent events reveal the potential for information technologies to threaten democratic participation and destabilize knowledge institutions. These are core concerns for researchers working within the area of critical information studies—yet these companies have also demonstrated novel tactics for obscuring their operations, reducing the ability of scholars to speak about how harms are perpetuated or to link them to larger systems. While scholars' methods and ethical conventions have historically privileged the agency of research participants, the current landscape suggests the value of exploring methods that would reveal actions that are purposefully hidden. We propose investigation as a model for critical information studies and review the methods and epistemological conventions of investigative journalists as a provocative example, noting that their orientation toward those in power enables them to discuss societal harms in ways that academic researchers often cannot. We conclude by discussing key topics, such as process accountability and institutional norms, that should feature in discussions of how academic researchers might position investigation in relation to their own work. [ABSTRACT FROM AUTHOR]

This study investigated the stability of Twitter counts of scientific publications over time. For this, we conducted an analysis of the availability statuses of over 2.6 million Twitter mentions received by the 1,154 most tweeted scientific publications recorded by Altmetric.com up to October 2017. The results show that of the Twitter mentions for these highly tweeted publications, about 14.3% had become unavailable by April 2019. Deletion of tweets by users is the main reason for unavailability, followed by suspension and protection of Twitter user accounts. This study proposes two measures for describing the Twitter dissemination structures of publications: Degree of Originality (i.e., the proportion of original tweets received by an article) and Degree of Concentration (i.e., the degree to which retweets concentrate on a single original tweet). Twitter metrics of publications with relatively low Degree of Originality and relatively high Degree of Concentration were observed to be at greater risk of becoming unstable due to the potential disappearance of their Twitter mentions. In light of these results, we emphasize the importance of paying attention to the potential risk of unstable Twitter counts, and the significance of identifying the different Twitter dissemination structures when studying the Twitter metrics of scientific publications. [ABSTRACT FROM AUTHOR]

We investigate the state of multilingualism across the social sciences and humanities (SSH) using a comprehensive data set of research outputs from seven European countries (Czech Republic, Denmark, Finland, Flanders [Belgium], Norway, Poland, and Slovenia). Although English tends to be the dominant language of science, SSH researchers often produce culturally and societally relevant work in their local languages. We collected and analyzed a set of 164,218 peer‐reviewed journal articles (produced by 51,063 researchers from 2013 to 2015) and found that multilingualism is prevalent despite geographical location and field. Among the researchers who published at least three journal articles during this time period, over one‐third from the various countries had written their work in at least two languages. The highest share of researchers who published in only one language were from Flanders (80.9%), whereas the lowest shares were from Slovenia (57.2%) and Poland (59.3%). Our findings show that multilingual publishing is an ongoing practice in many SSH research fields regardless of geographical location, political situation, and/or historical heritage. Here we argue that research is international, but multilingual publishing keeps locally relevant research alive with the added potential for creating impact. [ABSTRACT FROM AUTHOR]

The movement for open access publishing (OA) is often said to have its roots in the scientific disciplines, having been popularized by scientific publishers and formalized through a range of top‐down policy interventions. But there is an often‐neglected prehistory of OA that can be found in the early DIY publishers of the late 1980s and early 1990s. Managed entirely by working academics, these journals published research in the humanities and social sciences and stand out for their unique set of motivations and practices. This article explores this separate lineage in the history of the OA movement through a critical‐theoretical analysis of the motivations and practices of the early scholar‐led publishers. Alongside showing the involvement of the humanities and social sciences in the formation of OA, the analysis reveals the importance that these journals placed on experimental practices, critique of commercial publishing, and the desire to reach new audiences. Understood in today's context, this research is significant for adding complexity to the history of OA, which policymakers, advocates, and publishing scholars should keep in mind as OA goes mainstream. [ABSTRACT FROM AUTHOR]

Research activities related to social informatics (SI) are expanding, even as community fragmentation, topical dispersion, and methodological diversity continue to increase. Specifically, the different understandings of SI in regional communities have strong impacts, and each has a different history, methodological grounding, and often a different thematic focus. The aim of this article is to connect three selected perspectives on SI—intellectual (regional schools of thought), methodological, and thematic—and introduce a comparative framework for understanding SI that includes all known approaches. Thus, the article draws from a thematic and methodological grounding of research across schools of thought, along with definitions that rely on the extension and intension of the notion of SI. The article is built on a paralogy of views and pluralism typical of postmodern science. Because SI is forced to continually reform its research focus, due to the rapid development of information and communication technology, social changes and ideologies that surround computerization and informatization, the presented perspective maintains a high degree of flexibility, without the need to constantly redefine the boundaries, as is typical in modern science. This approach may support further developments in promoting and understanding SI worldwide. [ABSTRACT FROM AUTHOR]

The use of indicators and metrics for research evaluation purposes is well‐documented; however, less is known about their use by individual scholars. With a focus on the social sciences, this article contributes to the existing literature on indicators and metrics use in fields with diverse publication practices. Scholars in Australia and Sweden were asked about their use and reasons for using metrics. A total of 581 completed surveys were analyzed to generate descriptive statistics, with textual analysis performed on comments provided to open questions. While just under half of the participant group had used metrics, the Australians reported use in twice the proportion of their Swedish peers. Institutional policies and processes were frequently associated with use, and the scholars' comments suggest a high level of awareness of some metrics as well as strategic behavior in demonstrating research performance. There is also evidence of tensions between scholars' research evaluation environment and their disciplinary values and publication practices. [ABSTRACT FROM AUTHOR]

New types of digital data, tools, and methods, for instance those that cross academic disciplines and domains, those that feature teams instead of single scholars, and those that involve individuals from outside the academy, enables new forms of scholarship and teaching in digital humanities. Such scholarship promotes reuse of digital data, provokes new research questions, and cultivates new audiences. Digital curation, the process of managing a trusted body of information for current and future use, helps maximize the value of research in digital humanities. Predicated on semistructured interviews, this naturalistic case study explores the creation, use, storage, and planned reuse of data by 45 interviewees involved with 19 Office of Digital Humanities Start-Up Grant (SUG) projects. Interviewees grappled with challenges surrounding data, collaboration and communication, planning and project management, awareness and outreach, resources, and technology. Overall this study explores the existing digital curation practices and needs of scholars engaged in innovative digital humanities work and to discern how closely these practices and needs align with the digital curation literature. [ABSTRACT FROM AUTHOR]

The last 2 decades have witnessed a dramatic increase in the use of patent citation data in social science research. Facilitated by digitization of the patent data and increasing computing power, a community of practice has grown up that has developed methods for using these data to: measure attributes of innovations such as impact and originality; to trace flows of knowledge across individuals, institutions and regions; and to map innovation networks. The objective of this article is threefold. First, it takes stock of these main uses. Second, it discusses 4 pitfalls associated with patent citation data, related to office, time and technology, examiner, and strategic effects. Third, it highlights gaps in our understanding and offers directions for future research. [ABSTRACT FROM AUTHOR]

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method's unique advantages and drawbacks, as well as the broader roles that these methods play in the respective fields where they are often used. These insights allow us to make more informed decisions about the tradeoffs in choosing different methods for analyzing textual data. Furthermore, this comparison suggests ways that such methods might be combined in novel and compelling ways. [ABSTRACT FROM AUTHOR]

The introduction of new technologies and access to new information channels continue to change the way media studies researchers work and the questions they seek to answer. We investigate the current practices of media studies researchers and how these practices affect their research questions. Through the analysis of 27 interviews about the research practices of media studies researchers during a research project we developed a model of the activities in their research cycle. We find that information gathering and analysis activities are dominating the research cycle. These activities influence the research outcomes as they determine how research questions asked by media studies researchers evolve. Specifically, we show how research questions are related to the availability and accessibility of data as well as new information sources for contextualization of the research topic. Our contribution is a comprehensive account of the overall research cycle of media studies researchers as well as specific aspects of the research cycle, i.e., information sources, information seeking challenges, and the development of research questions. This work confirms findings of previous work in this area using a previously unstudied group of researchers, as well as providing new details about how research questions evolve. [ABSTRACT FROM AUTHOR]