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Identifying factors that associate with more cited or higher quality research may be useful to improve science or to support research evaluation. This article reviews evidence for the existence of such factors in article text and metadata. It also reviews studies attempting to estimate article quality or predict long‐term citation counts using statistical regression or machine learning for journal articles or conference papers. Although the primary focus is on document‐level evidence, the related task of estimating the average quality scores of entire departments from bibliometric information is also considered. The review lists a huge range of factors that associate with higher quality or more cited research in some contexts (fields, years, journals) but the strength and direction of association often depends on the set of papers examined, with little systematic pattern and rarely any cause‐and‐effect evidence. The strongest patterns found include the near universal usefulness of journal citation rates, author numbers, reference properties, and international collaboration in predicting (or associating with) higher citation counts, and the greater usefulness of citation‐related information for predicting article quality in the medical, health and physical sciences than in engineering, social sciences, arts, and humanities. [ABSTRACT FROM AUTHOR]

Value co‐creation as a research topic has been a critical proposition of interest to a wide range of disciplines. In recent years, the field of cultural heritage has also developed a range of information practices to promote different forms of value co‐creation. While the body of literature has begun to accumulate, we still lack a comprehensive understanding of conceptual foundations and how value co‐creation is implemented in cultural heritage information practices. This paper conducted a hermeneutic literature review to understand and conceptualize the core aspects of value co‐creation in various cultural heritage information works. In particular, this paper provides a research mapping of the genres of co‐creation in cultural heritage information practices, the actors, and the roles played by the stakeholders. Further, this review provides an overview of the dominant value co‐creation models in the cultural heritage field. It distills the drivers of value co‐creation and the core value consequences that arise from a process perspective. Finally, this paper puts forward a thematic, theoretical, and methodological agenda for future work based on these findings. The review contributes to the literature by proposing an integrated conceptual framework that summarizes the core elements of value co‐creation in cultural heritage information practices. The framework also serves as a call for action, providing a general understanding of the conceptual foundation for future research. [ABSTRACT FROM AUTHOR]

As a follow-up to the highly cited authors list published by Thomson Reuters in June 2014, we analyzed the top 1% most frequently cited papers published between 2002 and 2012 included in the Web of Science ( WoS) subject category 'Information Science & Library Science.' In all, 798 authors contributed to 305 top 1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly cited authors by Thomson Reuters in June 2014 (). Twelve of these 23 authors were involved in publishing 4 or more of the 305 papers under study. Analysis of coauthorship relations among the 798 highly cited scientists shows that coauthorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (a) collection and exploitation of information in clinical practices; (b) use of the Internet in public communication and commerce; and (c) scientometrics. [ABSTRACT FROM AUTHOR]

In recent years, the relationship of collaboration among scientists and the citation impact of papers have been frequently investigated. Most of the studies show that the two variables are closely related: An increasing collaboration activity (measured in terms of number of authors, number of affiliations, and number of countries) is associated with an increased citation impact. However, it is not clear whether the increased citation impact is based on the higher quality of papers that profit from more than one scientist giving expert input or other (citation-specific) factors. Thus, the current study addresses this question by using two comprehensive data sets with publications (in the biomedical area) including quality assessments by experts (F1000Prime member scores) and citation data for the publications. The study is based on more than 15,000 papers. Robust regression models are used to investigate the relationship between number of authors, number of affiliations, and number of countries, respectively, and citation impact-controlling for the papers' quality (measured by F1000Prime expert ratings). The results point out that the effect of collaboration activities on impact is largely independent of the papers' quality. The citation advantage is apparently not quality related; citation-specific factors (e.g., self-citations) seem to be important here. [ABSTRACT FROM AUTHOR]

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First‐time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first‐time collaboration increased after the outbreak of COVID‐19, and international collaboration witnessed a sudden decrease. During COVID‐19, papers with more first‐time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic. [ABSTRACT FROM AUTHOR]

Coauthorship prediction applies predictive analytics to bibliographic data to predict authors who are highly likely to be coauthors. In this study, we propose an approach for coauthorship prediction based on bibliographic network embedding through a graph‐based bibliographic data model that can be used to model common bibliographic data, including papers, terms, sources, authors, departments, research interests, universities, and countries. A real‐world dataset released by AMiner that includes more than 2 million papers, 8 million citations, and 1.7 million authors were integrated into a large bibliographic network using the proposed bibliographic data model. Translation‐based methods were applied to the entities and relationships to generate their low‐dimensional embeddings while preserving their connectivity information in the original bibliographic network. We applied machine learning algorithms to embeddings that represent the coauthorship relationships of the two authors and achieved high prediction results. The reference model, which is the combination of a network embedding size of 100, the most basic translation‐based method, and a gradient boosting method achieved an F1 score of 0.9 and even higher scores are obtainable with different embedding sizes and more advanced embedding methods. Thus, the strengths of the proposed approach lie in its customizable components under a unified framework. [ABSTRACT FROM AUTHOR]

This article provides the first historical analysis of the relationship between collaboration and scientific impact using three indicators of collaboration (number of authors, number of addresses, and number of countries) derived from articles published between 1900 and 2011. The results demonstrate that an increase in the number of authors leads to an increase in impact, from the beginning of the last century onward, and that this is not due simply to self-citations. A similar trend is also observed for the number of addresses and number of countries represented in the byline of an article. However, the constant inflation of collaboration since 1900 has resulted in diminishing citation returns: Larger and more diverse (in terms of institutional and country affiliation) teams are necessary to realize higher impact. The article concludes with a discussion of the potential causes of the impact gain in citations of collaborative papers. [ABSTRACT FROM AUTHOR]

The aim of this paper is to extend our knowledge about the power-law relationship between citation-based performance and coauthorship patterns in papers in the natural sciences. We analyzed 829,924 articles that received 16,490,346 citations. The number of articles published through coauthorship accounts for 89%. The citation-based performance and coauthorship patterns exhibit a power-law correlation with a scaling exponent of 1.20 ± 0.07. Citations to a subfield's research articles tended to increase 2.1.20 or 2.30 times each time it doubled the number of coauthored papers. The scaling exponent for the power-law relationship for single-authored papers was 0.85 ± 0.11. The citations to a subfield's single-authored research articles increased 2.0.85 or 1.89 times each time the research area doubled the number of single-authored papers. The Matthew Effect is stronger for coauthored papers than for single-authored. In fact, with a scaling exponent <1.0 the impact of single-authored papers exhibits a cumulative disadvantage or inverse Matthew Effect. [ABSTRACT FROM AUTHOR]

Power dynamics influence every aspect of scientific collaboration. Team power dynamics can be measured by team power level and team power hierarchy. Team power level is conceptualized as the average level of the possession of resources, expertise, or decision‐making authorities of a team. Team power hierarchy represents the vertical differences of the possessions of resources in a team. In Science of Science, few studies have looked at scientific collaboration from the perspective of team power dynamics. This research examines how team power dynamics affect team impact to fill the research gap. In this research, all coauthors of one publication are treated as one team. Team power level and team power hierarchy of one team are measured by the mean and Gini index of career age of coauthors in this team. Team impact is quantified by citations of a paper authored by this team. By analyzing over 7.7 million teams from Science (e.g., Computer Science, Physics), Social Sciences (e.g., Sociology, Library & Information Science), and Arts & Humanities (e.g., Art), we find that flat team structure is associated with higher team impact, especially when teams have high team power level. These findings have been repeated in all five disciplines except Art, and are consistent in various types of teams from Computer Science including teams from industry or academia, teams with different gender groups, teams with geographical contrast, and teams with distinct size. [ABSTRACT FROM AUTHOR]

Super‐partnerships exist between scholars connected within densely‐knit collaboration networks. Understanding how such relationships affect scholars' careers is of great importance. In this paper, focusing on the longitudinal aspects of scientific collaboration, we analyze collaboration profiles from the egocentric perspective and use analytic extreme value thresholds to identify super‐partners. A total of 5722 pairs of super‐partners are found in the field of economics. The several interesting findings about super‐partners are summarized as follows. (1) The collaboration pattern of super‐partners can be divided into three types: the dual‐core, bridge, and triangle types. (2) Gender disparities are reflected in the collaboration among super‐partners, and the stability of super‐partnerships involving different combinations of genders displays different characteristics. The random‐effect model is constructed to explore the effect of a super‐partnership on both parties from the aspects of productivity and influence, which also shows gender disparities. (3) A super‐partnership contributes to above‐average productivity and citation impacts of the publication for three collaboration patterns, and the research improvement of the triangle type is the greatest among the three types. Overall, this paper explores the characteristics of super‐partners and the added value of a long‐term commitment, which provides quantitative insights into the effect on scientific collaboration associated with close collaboration. [ABSTRACT FROM AUTHOR]

Generally, multicountry papers receive more citations than single-country ones. In this contribution, we examine if this rule also applies to American scientists publishing in highly visible interdisciplinary journals. Concretely, we compare the citations received by American scientists in N ature, S cience, and the P roceedings of the N ational A cademy of S ciences of the U nited S tates of A merica ( PNAS). It is shown that, statistically, American scientists publishing in N ature and S cience do not benefit from international collaboration. This statement also holds for communicated submissions, but not for direct and for contributed submissions, to PNAS. [ABSTRACT FROM AUTHOR]

There is increasing evidence that citations to Chinese research publications are rising sharply. A series of reasons have been highlighted in previous studies. This research explores another possibility-whether there is a 'clubbing' effect in China's surge in research citations, in which a higher rate of internal citing takes place among influential Chinese researchers. Focusing on the most highly cited research articles in nanotechnology, we find that a larger proportion of Chinese nanotechnology research citations are localized within individual, institutional, and national networks within China. Both descriptive and statistical tests suggest that highly cited Chinese papers are more likely than similar U.S. papers to receive internal and localized citations. Tentative explanations and policy implications are discussed. [ABSTRACT FROM AUTHOR]

This paper explores collaborative information behavior in the context of highly politicized decision making. It draws upon a qualitative case study of project management of a contentious public sector infrastructure project. We noted the creation of spaces for the development and exchange of information by experts and conceptualize these as information spheres. We postulate that these were formed to bypass power‐induced information behavior that excludes expert power, such as information avoidance. This approach contrasts with the expected project management and information norms, rules and behavior, however, provides a language that can be used to explain the phenomena of bounded information spaces which complement and may be used as a development of adjunct to small world's theory. [ABSTRACT FROM AUTHOR]

Common sense suggests that persistence is key to success. In academia, successful researchers have been found more likely to be persistent in publishing, but little attention has been given to how persistence in maintaining collaborative relationships affects career success. This paper proposes a new bibliometric understanding of persistence that considers the prominent role of collaboration in contemporary science. Using this perspective, we analyze the relationship between persistent collaboration and publication quality along several dimensions: degree of transdisciplinarity, difference in coauthor's scientific age and their scientific impact, and research‐team size. Contrary to traditional wisdom, our results show that persistent scientific collaboration does not always result in high‐quality papers. We find that the most persistent transdisciplinary collaboration tends to output high‐impact publications, and that those coauthors with diverse scientific impact or scientific ages benefit from persistent collaboration more than homogeneous compositions. We also find that researchers persistently working in large groups tend to publish lower‐impact papers. These results contradict the colloquial understanding of collaboration in academia and paint a more nuanced picture of how persistent scientific collaboration relates to success, a picture that can provide valuable insights to researchers, funding agencies, policy makers, and mentor–mentee program directors. Moreover, the methodology in this study showcases a feasible approach to measure persistent collaboration. [ABSTRACT FROM AUTHOR]

This article considers the interdisciplinary opportunities and challenges of working with digital cultural heritage, such as digitized historical newspapers, and proposes an integrated digital hermeneutics workflow to combine purely disciplinary research approaches from computer science, humanities, and library work. Common interests and motivations of the above‐mentioned disciplines have resulted in interdisciplinary projects and collaborations such as the NewsEye project, which is working on novel solutions on how digital heritage data is (re)searched, accessed, used, and analyzed. We argue that collaborations of different disciplines can benefit from a good understanding of the workflows and traditions of each of the disciplines involved but must find integrated approaches to successfully exploit the full potential of digitized sources. The paper is furthermore providing an insight into digital tools, methods, and hermeneutics in action, showing that integrated interdisciplinary research needs to build something in between the disciplines while respecting and understanding each other's expertise and expectations. [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]

In this opinion paper, we argue that global health crises are also information crises. Using as an example the coronavirus disease 2019 (COVID‐19) epidemic, we (a) examine challenges associated with what we term "global information crises"; (b) recommend changes needed for the field of information science to play a leading role in such crises; and (c) propose actionable items for short‐ and long‐term research, education, and practice in information science. [ABSTRACT FROM AUTHOR]

This study examines a range of factors associated with future citation and altmetric counts to a paper. The factors include journal impact factor, individual collaboration, international collaboration, institution prestige, country prestige, research funding, abstract readability, abstract length, title length, number of cited references, field size, and field type and will be modeled in association with citation counts, Mendeley readers, Twitter posts, Facebook posts, blog posts, and news posts. The results demonstrate that eight factors are important for increased citation counts, seven different factors are important for increased Mendeley readers, eight factors are important for increased Twitter posts, three factors are important for increased Facebook posts, six factors are important for increased blog posts, and five factors are important for increased news posts. Journal impact factor and international collaboration are the two factors that significantly associate with increased citation counts and with all altmetric scores. Moreover, it seems that the factors driving Mendeley readership are similar to those driving citation counts. However, the altmetric events differ from each other in terms of a small number of factors; for instance, institution prestige and country prestige associate with increased Mendeley readers and blog and news posts, but it is an insignificant factor for Twitter and Facebook posts. The findings contribute to the continued development of theoretical models and methodological developments associated with capturing, interpreting, and understanding altmetric events. [ABSTRACT FROM AUTHOR]

Scientific collaboration is essential in solving problems and breeding innovation. Coauthor network analysis has been utilized to study scholars' collaborations for a long time, but these studies have not simultaneously taken different collaboration features into consideration. In this paper, we present a systematic approach to analyze the differences in possibilities that two authors will cooperate as seen fromthe effects of homophily, transitivity, and preferential attachment. Exponential random graph models (ERGMs) are applied in this research. We find that different types of publications one author has written play diverse roles in his/her collaborations. An author's tendency to form new collaborations with her/his coauthors' collaborators is strong, where the more coauthors one author had before, the more new collaborators he/she will attract. We demonstrate that considering the authors' attributes and homophily effects as well as the transitivity and preferential attachment effects of the coauthorship network in which they are embedded helps us gain a comprehensive understanding of scientific collaboration. [ABSTRACT FROM AUTHOR]

The "sharing economy" has recently emerged as a major global phenomenon in practice and is consequently an important research topic. What, precisely, is meant by this term, "sharing economy"? The literature to date offers many, often incomplete and conflicting definitions. This makes it difficult for researchers to lead a coherent discourse, to compare findings and to select appropriate cases. Alternative terms (e.g., "collaborative consumption," "gig economy," and "access economy") are a further complication. To resolve this issue, our article develops a consolidated (based on all prior work) and systemic (relating to the phenomenon in its entire scope) definition of the sharing economy. The definition is based on the detailed analysis of definitions and explanations in 152 sources identified in a systematic literature review. We identify 36 original understandings of the term "sharing economy." Using semantic integration strategies, we consolidate 84 semantic facets in these definitions into 18 characteristics of the sharing economy. Resolving conflicts in the meaning and scope of these characteristics, we arrive at a consolidated, systemic definition. We evaluate the definition's appropriateness and applicability by applying it to cases claimed by the media to be examples of the sharing economy. This article's definition is useful for future research and discourse on the sharing economy. [ABSTRACT FROM AUTHOR]

This paper examines how shared affiliations within an institution (e.g., same primary appointment, same secondary appointment, same research center, same laboratory/facility) and physical proximity (e.g., walking distance between collaborator offices) shape knowledge creation through biomedical science collaboration in general, and interdisciplinary collaboration in particular. Using archival and publication data, we examine pairwise research collaborations among 1,138 faculty members over a 12‐year period at a medical school in the United States. Modeling at the dyadic level, we find that faculty members with more shared institutional affiliations are positively associated with knowledge creation and knowledge impact, and that this association is moderated by the physical proximity of collaborators. We further find that the positive influence of disciplinary diversity (e.g., collaborators from different fields) on knowledge impact is stronger among pairs that share more affiliations and is significantly reduced as the physical distance among collaborators increases. These results support the idea that shared institutional affiliations and physical proximity can increase interpersonal contact, providing more opportunities to develop trust and mutual understanding, and thus alleviating some of the coordination issues that can arise with higher disciplinary diversity. We discuss the implications for future research on scientific collaborations, managerial practice regarding office space allocation, and strategic planning of initiatives aimed at promoting interdisciplinary collaboration. [ABSTRACT FROM AUTHOR]

In a range of scientific coauthorship networks, transitions emerge in degree distribution, in the correlation between degree and local clustering coefficient, etc. The existence of those transitions could be regarded because of the diversity in collaboration behaviors of scientific fields. A growing geometric hypergraph built on a cluster of concentric circles is proposed to model two specific collaboration behaviors, namely the behaviors of research team leaders and those of the other team members. The model successfully predicts the transitions, as well as many common features of coauthorship networks. Particularly, it realizes a process of deriving the complex “scale‐free” property from the simple “yes/no” decisions. Moreover, it provides a reasonable explanation for the emergence of transitions with the difference of collaboration behaviors between leaders and other members. The difference emerges in the evolution of research teams, which synthetically addresses several specific factors of generating collaborations, namely the communications between research teams, academic impacts and homophily of authors. [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]

Although the open access citation advantage (OACA) has been discussed extensively, scholars lack a clear understanding of the mechanisms through which switching from subscription‐based model to open access (OA) model affects the citation impact of a scholarly journal. Many journals have switched from subscription to OA, yet they later also flipped their preswitching articles (i.e., those under subscription model) to OA, thus leaving no subscription article to be compared with their postswitching OA counterparts. To detect the switching effect, our study instead focused on 60 journals that "reverse flipped" from OA to subscription. We use a difference‐in‐difference (DiD) analytical framework to analyze two propositions related to OACA, based on the bibliographic and citation data of pre‐ and postswitching publications in these journals. Our findings indicate that reverse flipping is unlikely to affect the journals' impact through changing the visibility of their articles. Instead, it could lead to a systematical shift in the submissions to the journals and thus considerably affect their impact. Our findings have important theoretical and practical implications for subsequent studies, funding agencies, and scholarly journals considering a reverse flip. [ABSTRACT FROM AUTHOR]

Brazilian scholarly output has rapidly increased, accompanied by the expansion of domestic collaborations. In this paper, we identify spatial patterns of collaboration in Brazil and measure the role of geographic proximity in determining the interaction among researchers. Using a database comprising more than one million researchers and seven million publications, we consolidated information on interregional research collaboration in terms of scientific coauthorship networks among 4,615 municipalities during the period between 1992 and 2009, which allowed us to analyze a range of data unprecedented in the literature. The effects of geographic distance on collaboration were measured for different areas by estimating spatial interaction models. The main results provide strong evidence of geographic deconcentration of collaboration in recent years, with increased participation of authors in scientifically less traditional regions, such as south and northeast Brazil. Distance remains a significant factor in determining the intensity of knowledge flow in collaboration networks in Brazil, as an increase of 100 km between two researchers reduces the probability of collaboration by an average of 16%, and there is no evidence that the effect of distance has diminished over time, although the magnitude of such effects varies among networks of different areas. [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]

Collaborative Computer- Supported Argument Visualization ( CCSAV) has often been proposed as an alternative over more conventional, mainstream platforms for online discussion (e.g., online forums and wikis). CCSAV tools require users to contribute to the creation of a joint artifact (argument map) instead of contributing to a conversation. In this paper we assess empirically the effects of this fundamental design choice and show that the absence of conversational affordances and socially salient information in representation-centric tools is detrimental to the users' collaboration experience. We report empirical findings from a study in which subjects using different collaborative platforms (a forum, an argumentation platform, and a socially augmented argumentation tool) were asked to discuss and predict the price of a commodity. By comparing users' experience across several metrics we found evidence that the collaborative performance decreases gradually when we remove conversational interaction and other types of socially salient information. We interpret these findings through theories developed in conversational analysis (common ground theory) and communities of practice and discuss design implications. In particular, we propose balancing the trade-off between knowledge reification and participation in representation-centric tools with the provision of social feedback and functionalities supporting meaning negotiation. [ABSTRACT FROM AUTHOR]

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self‐citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014–20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2–0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields. [ABSTRACT FROM AUTHOR]

Automated text categorization methods are of broad relevance for domain experts since they free researchers and practitioners from manual labeling, save their resources (e.g., time, labor), and enrich the data with information helpful to study substantive questions. Despite a variety of newly developed categorization methods that require substantial amounts of annotated data, little is known about how to build models when (a) labeling texts with categories requires substantial domain expertise and/or in‐depth reading, (b) only a few annotated documents are available for model training, and (c) no relevant computational resources, such as pretrained models, are available. In a collaboration with environmental scientists who study the socio‐ecological impact of funded biodiversity conservation projects, we develop a method that integrates deep domain expertise with computational models to automatically categorize project reports based on a small sample of 93 annotated documents. Our results suggest that domain expertise can improve automated categorization and that the magnitude of these improvements is influenced by the experts' understanding of categories and their confidence in their annotation, as well as data sparsity and additional category characteristics such as the portion of exclusive keywords that can identify a category. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) reconfigures work and organization, while work and organization shape AI. In this special issue, we explore these mutual transformations and how they play out across industries and occupations. We argue that, to truly appreciate this transformative power, the use of AI should be understood in relation to key dimensions of the work context. In this editorial, we discuss the sociotechnical dynamics of AI implementation, the research landscape of AI in the context of work, and key contextual factors on the macro‐ and micro‐level that help understand the AI‐work nexus. We then provide directions for future research at the intersection of work and AI. [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]

Changes in modes of publication over recent decades and moves to publish material freely and openly have resulted in increased amounts of research and scholarly outputs being available online. These include teaching and other material but consist mostly of research publications. There have been significant UK and European initiatives as part of the Open Agenda that facilitate and indeed mandate the move to open whether that is for educational materials, research output and data, or the mechanisms for ensuring the quality of these materials. A significant issue is that although making research outputs freely available is praiseworthy, without the data on which that research is based, reproducibility and so verification, which are fundamental principles of scholarly methodology, are not possible. When discrete datasets are linked openly and freely, are able to interact by using common standards, they become more powerful with extended possibilities for research questions that cross disciplinary divides and knowledge domains. There are always objections and resistance to new innovations, and open publication is no exception; published research, nevertheless, indicates that publishing material openly is becoming considered to be "good research practice" and that the positives of "new collaborations and higher citation" outweigh any perceived negative effects. [ABSTRACT FROM AUTHOR]

Despite large public investments in facilitating the secondary use of data, there is little information about the specific factors that predict data's reuse. Using data download logs from the Inter‐university Consortium for Political and Social Research (ICPSR), this study examines how data properties, curation decisions, and repository funding models relate to data reuse. We find that datasets deposited by institutions, subject to many curatorial tasks, and whose access and preservation is funded externally, are used more often. Our findings confirm that investments in data collection, curation, and preservation are associated with more data reuse. [ABSTRACT FROM AUTHOR]

Biochemistry is a highly funded research area that is typified by large research teams and is important for many areas of the life sciences. This article investigates the citation impact and Mendeley readership impact of biochemistry research from 2011 in the Web of Science according to the type of collaboration involved. Negative binomial regression models are used that incorporate, for the first time, the inclusion of specific countries within a team. The results show that, holding other factors constant, larger teams robustly associate with higher impact research, but including additional departments has no effect and adding extra institutions tends to reduce the impact of research. Although international collaboration is apparently not advantageous in general, collaboration with the United States, and perhaps also with some other countries, seems to increase impact. In contrast, collaborations with some other nations seems to decrease impact, although both findings could be due to factors such as differing national proportions of excellent researchers. As a methodological implication, simpler statistical models would find international collaboration to be generally beneficial and so it is important to take into account specific countries when examining collaboration. [ABSTRACT FROM AUTHOR]

On account of the complexities related to the use of digitized newspapers, researchers may encounter barriers when interacting with the collections' content. Overcoming barriers that could influence their information interaction should enhance the accessibility and utility of the newspapers. Hence, the study examined the barriers faced in history‐research tasks involving interaction with digitized historical newspapers, with focus on the barriers' contexts and the related task‐based activities. The analysis employed two datasets, from in‐depth interviews and demonstrations of newspaper‐use situations. Content analysis from these complementary data showed that barriers arose in multiple contexts, connected with the collection, task, tools, and socio‐organizational setting. Most barriers were associated with collection context and occurred in information searching and selection activities and in working with information items. Barriers related to the task or to socio‐organizational context arose most often in the planning and monitoring activities and in synthesizing and reporting. Such research‐based insight into the barriers faced can aid in illuminating what is required for providing good support to researchers working with digital newspaper content. [ABSTRACT FROM AUTHOR]

Despite being necessary, keeping up to date with new information and trends remains challenging in many fields due to information overload, time constraints, and insufficient evaluation skills. Collaboration, or sharing the effort among group members, may be a solution, but more knowledge is needed. To guide future research on the potential role of collaboration in keeping up to date, we conducted a systematic literature review with a framework synthesis aimed to adapt the conceptual framework for environmental scanning to a collaborative context. Our specific objectives were to identify the factors and outcomes of collaborative information seeking (CIS) and use them to propose an adapted conceptual framework. Fifty‐one empirical studies were included and synthesized using a hybrid thematic synthesis. The adapted framework includes seven types of influencing factors and five types of outcomes. Our review contributes to the theoretical expansion of knowledge on CIS in general and provides a conceptual framework to study collaboration in keeping up to date. Overall, our findings will be useful to researchers, practitioners, team leaders, and system designers implementing and evaluating collaborative information projects. [ABSTRACT FROM AUTHOR]

Loan processors and underwriters at mortgage firms seek to gather substantial supporting documentation to properly understand and model loan risks. In doing so, loan originations become prone to closing delays, risking client dissatisfaction and consequent revenue losses. We collaborate with a large national mortgage firm to examine the extent to which these delays are predictable, using internal discussion threads to prioritize interventions for loans most at risk. Substantial work experience is required to predict delays, and we find that even highly trained employees have difficulty predicting delays by reviewing discussion threads. We develop an array of methods to predict loan delays. We apply four modern out‐of‐the‐box sentiment analysis techniques, two dictionary‐based and two rule‐based, to predict delays. We contrast these approaches with domain‐specific approaches, including firm‐provided keyword searches and "smoke terms" derived using machine learning. Performance varies widely across sentiment approaches; while some sentiment approaches prioritize the top‐ranking records well, performance quickly declines thereafter. The firm‐provided keyword searches perform at the rate of random chance. We observe that the domain‐specific smoke term approaches consistently outperform other approaches and offer better prediction than loan and borrower characteristics. We conclude that text mining solutions would greatly assist mortgage firms in delay prevention. [ABSTRACT FROM AUTHOR]

An editorial is presented on marking out the area of digital humanities (DH). Topics include suggesting further areas of study such as analysis of conferences and citations as well as diachronic representations of the ever-developing landscape of DH; and developing an integrated digital hermeneutics workflow combining research approaches from computer science and the humanities.

The interdisciplinary field known as digital humanities (DH) is represented in various forms in the teaching and research practiced in iSchools. Building on the work of an iSchools organization committee charged with exploring digital humanities curricula, we present findings from a series of related studies exploring aspects of DH teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Through a survey of iSchool programs and an online DH course registry, we investigate the various education models for DH training found in iSchools, followed by a detailed look at DH courses and curricula, explored through analysis of course syllabi and course descriptions. We take a brief look at collaborative disciplines with which iSchools cooperate on DH research projects or in offering DH education. Next, we explore DH careers through an analysis of relevant job advertisements. Finally, we offer some observations about the management and administrative challenges and opportunities related to offering a new iSchool DH program. Our results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives. [ABSTRACT FROM AUTHOR]

Collaborator recommendation is of great significance for facilitating research collaboration. Proximities have been demonstrated to be significant factors and determinants of research collaboration. Research leadership is associated with not only the capability to integrate resources to launch and sustain the research project but also the production and academic impact of the collaboration team. However, existing studies mainly focus on social or cognitive proximity, failing to integrate critical proximities comprehensively. Besides, existing studies focus on recommending relationships among all the coauthors, ignoring leadership in research collaboration. In this article, we propose a proximity‐aware research leadership recommendation (PRLR) model to systematically integrate critical node attribute information (critical proximities) and network features to conduct research leadership recommendation by predicting the directed links in the research leadership network. PRLR integrates cognitive, geographical, and institutional proximity as node attribute information and constructs a leadership‐aware coauthorship network to preserve the research leadership information. PRLR learns the node attribute information, the local network features, and the global network features with an autoencoder model, a joint probability constraint, and an attribute‐aware skip‐gram model, respectively. Extensive experiments and ablation studies have been conducted, demonstrating that PRLR significantly outperforms the state‐of‐the‐art collaborator recommendation models in research leadership recommendation. [ABSTRACT FROM AUTHOR]

Although Washington state sanctuary policies of 2017 prohibit collaboration between local law enforcement and federal immigration enforcement in noncriminal cases, compliance with sanctuary policies has not been systematically studied. We explore information practices and collaboration between local law enforcement and federal immigration enforcement in Grant County, Washington, based on records from November 2017 to May 2019 obtained by the University of Washington Center for Human Rights through Public Records Act (PRA) requests. Qualitative analysis of over 8,000 pages reveals a baseline of passive and active information sharing and collaboration between local law enforcement and federal immigration agencies before Washington sanctuary laws went into effect in May 2019, a practice that needs to stop if agencies are to comply with the laws. We employ a systematic methodology to obtain (through PRA and other Access to Information requests) and analyze official records through qualitative content analysis, to monitor and hold local law enforcement accountable in their compliance with sanctuary laws. This method can be used to examine law enforcement information behaviors in other counties in Washington, and in other states that offer sanctuary protections, as a way to monitor compliance with sanctuary laws and strengthen the protection of immigrants' rights. [ABSTRACT FROM AUTHOR]

The preservation of the scholarly record has been a point of concern since the beginning of knowledge production. With print publications, the responsibility rested primarily with librarians, but the shift toward digital publishing and, in particular, the introduction of open access (OA) have caused ambiguity and complexity. Consequently, the long‐term accessibility of journals is not always guaranteed, and they can even disappear from the web completely. The focus of this exploratory study is on the phenomenon of vanished journals, something that has not been carried out before. For the analysis, we consulted several major bibliographic indexes, such as Scopus, Ulrichsweb, and the Directory of Open Access Journals, and traced the journals through the Internet Archive's Wayback Machine. We found 174 OA journals that, through lack of comprehensive and open archives, vanished from the web between 2000 and 2019, spanning all major research disciplines and geographic regions of the world. Our results raise vital concern for the integrity of the scholarly record and highlight the urgency to take collaborative action to ensure continued access and prevent the loss of more scholarly knowledge. We encourage those interested in the phenomenon of vanished journals to use the public dataset for their own research. [ABSTRACT FROM AUTHOR]

Knowledge order in an online knowledge community (OKC) refers to a consensual version of collective knowledge in the creation of shared knowledge representation. Much previous research has been conducted in the context of the ordered structure of objective knowledge systems, but this does little to explain the microlevel order of knowledge after users contribute knowledge and achieve consensus through online interactions in OKC. Based on interactive team cognition theory and the stigmergy coordination mechanism, our research aims to investigate how knowledge and experience heterogeneity affect knowledge order effectiveness and efficiency through collaborative and communicative interaction. To test our hypotheses, we randomly collected the records of 250 articles from the English version of Wikipedia. Partial least squares structural equation modeling indicated that OKC favoring online collective knowledge order by limiting communicative interaction, as collaborative interaction is very effective in achieving knowledge order and in achieving it in a fast way. From our findings, scholars and practitioners are advised to pay attention to online knowledge order in the management and design of OKC. [ABSTRACT FROM AUTHOR]