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This paper presents an analysis of a hundred and one handwritten essays by master students in Informatics. The students reflected on their experiences of working with pen and paper for reading and writing as a mandatory assignment for the duration of a five-week intensive course. Taking an inductive approach, reflexive thematic analysis was used to identify patterns of meaning across the full dataset. The essays elicited insightful student reflections on learning, knowing, and being. One overarching theme, New connections, and four sub-theses were identified: Handwriting as note making, Being present for learning, Freedom to think, and Materiality of reading and writing. This study contributes to an improved understanding of the affordances of paper and laptops in the lecture room, based on a student-centred approach, and reflects on how student perspectives can be implemented during lectures.

Subject to various restrictive requirements on project application and completion, funded projects are often affected by funding policies for the selection of research objects. This study explored the impact of scientific research funding policies on the funding and research by comparing the topic distribution of awards and papers. A total of 1,870 awards and 16,491 papers of the National Social Science Foundation of China (NSSFC) in library and information science (LIS) were collected from a Chinese research project database. According to the results, the growth rate of awards on most topics is higher than that of papers, while the growth rate of papers on the relevant topics to users, technology, and metrology is higher than that of awards. It was found out in the study that the topics funded by NSSFC were imbalanced. NSSFC provides much more funding to traditional topics rather than emerging topics. As indicated by the funding provided to the projects on traditional topics for research on a large number of papers on emerging topics, however, the innovation and diversity of academic research have yet to be restricted. This study demonstrated that the effect of funding policies on the research topics in LIS is significant. Topic suggestions and funding structure of NSSFC have more impacts on award topics than on paper topics. The influence of NSSFC-recommended topics on paper topics is declining year by year. Additionally, awards with high funding intensity are more susceptible to topic suggestions.

Purpose: Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly cited paper prediction studies consider early citation information, so predicting highly cited papers by publication is challenging. Therefore, the authors propose a method for predicting early highly cited papers based on their own features. Design/methodology/approach: This research analyzed academic papers published in the Journal of the Association for Computing Machinery (ACM) from 2000 to 2013. Five types of features were extracted: paper features, journal features, author features, reference features and semantic features. Subsequently, the authors applied a deep neural network (DNN), support vector machine (SVM), decision tree (DT) and logistic regression (LGR), and they predicted highly cited papers 1–3 years after publication. Findings: Experimental results showed that early highly cited academic papers are predictable when they are first published. The authors' prediction models showed considerable performance. This study further confirmed that the features of references and authors play an important role in predicting early highly cited papers. In addition, the proportion of high-quality journal references has a more significant impact on prediction. Originality/value: Based on the available information at the time of publication, this study proposed an effective early highly cited paper prediction model. This study facilitates the early discovery and realization of the value of scientific and technological achievements. [ABSTRACT FROM AUTHOR]

The author was assigned the task to comment on the broad topic: "New sciences, technologies, and media--impact on education for librarianship (or libraries)." The author choose to emphasize "information science." Narrowing the subject down even further, in this article the author emphasizes some of the aspects of the "interface" between librarianship and information science, where he believes the action is going to develop in the coming years. [For the commentary on this article, "Broad and Visionary. Commentary on Allen Kent (1977) Information Science," see EJ1073522. This article was originally published in the "Journal of Education for Librarianship" (1977).]

The study compared the bibliometric parameters of scholarly communications published in COLLNET Journal of Scientometrics & Information Management (CJSIM) and Journal of Scientometric Research (JSR) from 2012 to 2021. Different bibliometric parameters examined in the study are pattern of output during 2012 to 2021, identification of most prolific countries and their citation impact in terms of Citation Per Paper (CPP), i-10 index and Papers not Cited (PnC). Study also identified prolific institutions and authors and their citation impact besides examining pattern of citation. The study also examined the pattern of domestic and international collaboration. Findings of the study indicate that the pattern of output is inconsistent in both the journals. The output is scattered among 39 countries in CJSIM and 50 countries in JSR. India followed by Iran contributed the highest number of papers in both the journals. Most of the prolific institutions and authors were from India in both the journals. More number of papers remained uncited in CJSIM as compared to JSR. More number of papers were published in domestic collaboration in JSR as compared to CJSIM. However, papers published in international collaboration in both the journals was almost equal. Among all the countries, China published the highest number of papers in international collaboration in CJSIM, but no such trend was observed in JSR. [ABSTRACT FROM AUTHOR]

This article provides a scoping review of 25 years of research on the notion of cognitive authority (CA), examining its conceptualization and empirical examination. The review follows the PRISMA statement and its extension for scoping reviews. Peer‐reviewed journal articles on CA were identified through database searching with the specific search term “cognitive authorit*” in the title or abstract and covering work published in 2022 or earlier. In total, 235 unique references were identified, and their abstracts and then selected full texts were screened according to predetermined exclusion criteria. In total, 40 articles were included in the review, extracted, and analyzed with qualitative content analysis focusing on the conceptualization of CA, the methodological approach taken to examine it, and the different spheres of knowledge and levels of activity the research addressed. Based on this analysis, four parallel lines of research were identified including studies conceptualizing CA: (1) as an indicator of information source quality, (2) as discursively constructed, (3) as situated in social mechanisms and settings, and (4) as institutional legitimacy of science and professions. This body of research has extended Wilson's (1983; Second‐hand knowledge: An inquiry into cognitive authority. Greenwood Press) original work contributing to our understanding of CA at individual, communal, and societal levels. [ABSTRACT FROM AUTHOR]

Research on how people look for and interact with information has a long history in the information field. The current literature has been repeatedly reviewed in earlier volumes of Annual Review of Information Science and Technology. In this review, we offer an overview of the research published in this area in the years 2016–2022 with a focus on the trends that have emerged in this period. We use the term “information behavior” as an umbrella for the research area interested in how people become informed and engage with information in diverse manners acknowledging that different researchers and subfields prefer other terms and frameworks, including information practices, information experience, and health information seeking, to name a few. We reviewed 1270 articles in the field published in the years 2016–2022 and identified seven emerging trends: The CoVID‐19 Pandemic, Diversity and Inclusion, Embodiment, Misinformation and Trust, Social Q&A Websites, Collaboration, and Information Creation. The reviewed literature and trends are discussed in relation to their significance for information, earlier review of information behavior research, and the long‐debated issue of theory‐driven versus atheoretical research in the field. [ABSTRACT FROM AUTHOR]

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]

The Journal of Geographical Systems (JGS) has announced two initiatives to recognize outstanding research published in the journal. The first initiative is the JGS Best Paper Award, which aims to encourage and acknowledge excellent scholarship in the field of GIScience and spatial planning. The second initiative is the Editors' Choice, where the editors select their favorite paper from each issue. The winners of these awards are listed on the journal's website and their papers are made freely accessible for a certain period of time. The 2023 JGS Best Paper Award was given to Luyu Liu, Adam Porr, and Harvey J. Miller for their research on evaluating the reliability of public transit accessibility using real-time data. The paper demonstrates how even small levels of unreliability in transit services can significantly impact accessibility levels, particularly for lower income populations. The paper also promotes open and reproducible research practices. The Editors' Choice for Volume 26(1) is a paper by Chris Jacobs-Crisioni, Ana I. Moreno-Monroy, Mert Kompil, and Lewis Dijkstra, which proposes a sequential approach to estimate school provision, cost, and access using open databases of student counts. The paper provides valuable insights into the balance between cost, access, and residential values in school provision. Both papers are recognized for their significant contributions to the field. [Extracted from the article]

The gig economy and gig work have grown quickly in recent years and have drawn much attention from researchers in different fields. Because the platform mediated gig economy is a relatively new phenomenon, studies have produced a range of interesting findings; of interest here are the socio‐technical issues that this work has surfaced. This systematic literature review (SLR) provides a snapshot of a range of socio‐technical issues raised in the last 12 years of literature focused on the platform mediated gig economy. Based on a sample of 515 papers gathered from nine databases in multiple disciplines, 132 were coded that specifically studied the gig economy, gig work, and gig workers. Three main socio‐technical themes were identified: (1) the digital workplace, which includes information infrastructure and digital labor that are related to the nature of gig work and the user agency; (2) algorithmic management, which includes platform governance, performance management, information asymmetry, power asymmetry, and system manipulation, relying on a diverse set of technological tools including algorithms and big data analytics; (3) ethical design, as a relevant value set that gig workers expect from the platform, which includes trust, fairness, equality, privacy, and transparency. A social informatics perspective is used to rethink the relationship between gig workers and platforms, extract the socio‐technical issues noted in prior research, and discuss the underexplored aspects of the platform mediated gig economy. The results draw attention to understudied yet critically important socio‐technical issues in the gig economy that suggest short‐ and long‐term opportunities for future research directions. [ABSTRACT FROM AUTHOR]

While bibliographic classifications are traditionally based on disciplines, the logical alternative is phenomenon‐based classification. Although not prevalent, this approach has been explored in the 20th century by J.D. Brown, the Classification Research Group, and others. Its principles have been stated in the León Manifesto (2007) and are currently represented by such general schemes as the Basic Concepts Classification and the Integrative Levels Classification. A phenomenon‐based classification lists classes of phenomena, including things and processes irrespective of the discipline studying them (which can optionally be specified as an additional facet). Facets can work in a phenomenon‐based system much as in a disciplinary one. This kind of system will promote the identification of potential relationships between research in different disciplines, and will especially benefit interdisciplinary work. The paper reviews the theory, history, structure, advantages, applications, and evaluation of phenomenon‐based classification systems. [ABSTRACT FROM AUTHOR]

• We classified the field normalization methods into linear and nonlinear methods. • Nonlinear field normalization citation counts should not be added or averaged. • We analyzed why the nonlinear normalized citations should not be added or averaged. • We provided mathematical proofs for the crucial steps of the above analysis. • Our mathematical proof is applicable to all nonlinear data in real number domain. Nonlinear field normalization citation counts at the paper level obtained using nonlinear field normalization methods should not be added or averaged. Unfortunately, there are many cases adding or averaging the nonlinear normalized citation counts of individual papers that can be found in the academic literature, indicating that nonlinear field normalization methods have long been misused in academia. In this paper, we performed the following three research works. First, we analyzed why the nonlinear normalized citation counts of individual papers should not be added or averaged from the perspective of theoretical analysis in mathematics: we provided mathematical proofs for the crucial steps of the analysis. Second, we systematically classified the existing main field normalization methods into linear and nonlinear field normalization methods. Third, we used real citation data to explore the error effects caused by adding or averaging the nonlinear normalized citation counts on practical research evaluation results. The above three research works provide a theoretical basis for the proper use of field normalization methods in the future. Furthermore, because our mathematical proof is applicable to all nonlinear data in the entire real number domain, our research works are also meaningful for the whole field of data and information science. [ABSTRACT FROM AUTHOR]

The aim of this article is to explore up to seven parameters related to the methodological quality and reproducibility of thematic bibliometric research published in the two most productive journals in bibliometrics, Sustainability (a journal outside the discipline) and Scientometrics, the flagship journal in the field. The study identifies the need for developing tailored tools for improving the quality of thematic bibliometric analyses, and presents a framework that can guide the development of such tools. A total of 508 papers are analysed, 77% of Sustainability, and 23% published in Scientometrics, for the 2019-2021 period. An average of 2.6 shortcomings per paper was found for the whole sample, with an almost identical number of flaws in both journals. Sustainability has more flaws than Scientometrics in four of the seven parameters studied, while Scientometrics has more shortcomings in the remaining three variables. The first limitation of this work is that it is a study of two scientific journals, so the results cannot be directly extrapolated to the set of thematic bibliometric analyses published in journals from all fields. We propose the adoption of protocols, guidelines, and other similar tools, adapted to bibliometric practice, which could increase the thoroughness, transparency, and reproducibility of this type of research. These results show considerable room for improvement in terms of the adequate use and breakdown of methodological procedures in thematic bibliometric research, both in journals in the Information Science area and journals outside the discipline. [ABSTRACT FROM AUTHOR]

Death is an inevitable part of life and highly relevant to information management: its approach often requires preparation, and its occurrence often demands a response. Many works in information science have acknowledged so much, and yet death is rarely a focused topic, appearing instead sporadically and disconnected across research. As a result there is no introduction to, overview of, or synthesis across studies on death and information. We therefore conducted an extensive literature search and reviewed nearly 300 scholarly publications at the intersection of death and information (and data) management. Covering seven topics in total, we review two groups of work directly engaging information management in relation to death (digital possessions, inheritance, and legacy; information behavior, needs, and practices around death), three engaging death and technology that require information and its management (death and the Internet, thanatosensitive design and technology‐augmented death practices, and the digital afterlife and digital immortality), and two reflecting the ethical and legal dimensions unique to death and information. We then integrate the collective findings to summarize the landscape of death‐related information research, outline remaining challenges for individuals, families, institutions, and society, and identify promising directions for future information science research. [ABSTRACT FROM AUTHOR]

Reviews have long been recognized as among the most important forms of scientific communication. The rapid growth of the primary literature has further increased the need for reviews to distill and interpret the literature. This review on Reviews and Reviewing: Approaches to Research Synthesis encompasses the evolution of the review literature, taxonomy of review literature, uses and users of reviews, the process of preparing reviews, assessment of review quality and impact, the impact of information technology on the preparation of reviews, and research opportunities for information science related to reviews and reviewing. In addition to providing a synthesis of prior research, this review seeks to identify gaps in the published research and to suggest possible future research directions. [ABSTRACT FROM AUTHOR]

Data culture/s as a research topic has begun to attract attention from a wide range of disciplines, albeit with inconsistent application of definitions, dimensions, and applications. This work builds on a call to investigate data culture/s within the information studies domain as a topic related to, but distinct from, information culture. The purpose of this study is to explore what is known about data culture/s in greater depth. We apply a retroductive approach to select and consider likely dimensions, inputs, and aspects of data culture/s in order to further map this construct to the literature, and thereby highlight gaps and opportunities to add to this body of knowledge. The initial candidate dimensions explored below include data‐related skills and attitudes, data sharing, data use/reuse, data ethics and governance, and a specific focus on Indigenous perspectives to provide insights on why and how a group may contest the emergent dominant discourse of data culture/s. Our conclusion highlights areas needing further research to fully define and examine the dimensions, inputs, and aspects of data culture/s, and calls for greater understanding and engagement with data culture/s from the information studies community. [ABSTRACT FROM AUTHOR]

Examines the characteristics of rejected manuscripts submitted to the "African Journal of Library, Archives and Information Science." Most of the papers were rejected because they contributed nothing new to knowledge (65.5%), used unreliable data (13.1%) and lacked focus (13.1%). There were no remarkable differences with regard to status and affiliations between authors of rejected and accepted papers. (Author/AEF)

Subject to various restrictive requirements on project application and completion, funded projects are often affected by funding policies for the selection of research objects. This study explored the impact of scientific research funding policies on the funding and research by comparing the topic distribution of awards and papers. A total of 1,870 awards and 16,491 papers of the National Social Science Foundation of China (NSSFC) in library and information science (LIS) were collected from a Chinese research project database. According to the results, the growth rate of awards on most topics is higher than that of papers, while the growth rate of papers on the relevant topics to users, technology, and metrology is higher than that of awards. It was found out in the study that the topics funded by NSSFC were imbalanced. NSSFC provides much more funding to traditional topics rather than emerging topics. As indicated by the funding provided to the projects on traditional topics for research on a large number of papers on emerging topics, however, the innovation and diversity of academic research have yet to be restricted. This study demonstrated that the effect of funding policies on the research topics in LIS is significant. Topic suggestions and funding structure of NSSFC have more impacts on award topics than on paper topics. The influence of NSSFC-recommended topics on paper topics is declining year by year. Additionally, awards with high funding intensity are more susceptible to topic suggestions. [ABSTRACT FROM AUTHOR]

This article offers comments and clarifications of Egghe's paper, which dealt with information production processes (IPP) and the Gini index. Topics addressed include the length of the Lorenz curve as a concentration measure, the discrete duality operator, and a Bradford-Leimkuhler distribution. (10 references) (LRW)

The paper analysed 699 papers published in Library & Information Science Research (LISR) during the period of 1994-2020. Google Scholar was used to obtain the number of citations received by these papers until April 30, 2021. The study examined the geographical distribution of published articles and also identified prolific institutions and authors. The study examined the impact of output of countries, institutions and authors using citation per paper (CPP) and i-10 index as indicators of impact. The study also examined the pattern of growth and identified the highly cited papers. Based on the analysis of data it is observed that maximum articles were published during the three years block of 2015-2017. The geographical distribution of output indicates that 51 countries contributed the 699 papers. Highest number of papers was contributed by authors from the USA though it had a low value of CPP in comparison to Norway and Finland. Among the institutions, Florida State University (USA) topped the list. However, University of Illinois at Urbana-Champaign, USA had the highest value of CPP. During the period of study, 1,389 papers received 74,061 citations, of which only 41 (3 %) articles remained uncited. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of a hundred and one handwritten essays by master students in Informatics. The students reflected on their experiences of working with pen and paper for reading and writing as a mandatory assignment for the duration of a five-week intensive course. Taking an inductive approach, reflexive thematic analysis was used to identify patterns of meaning across the full dataset. The essays elicited insightful student reflections on learning, knowing, and being. One overarching theme, New connections, and four sub-theses were identified: Handwriting as note making, Being present for learning, Freedom to think, and Materiality of reading and writing. This study contributes to an improved understanding of the affordances of paper and laptops in the lecture room, based on a student-centred approach, and reflects on how student perspectives can be implemented during lectures. [ABSTRACT FROM AUTHOR]

Purpose: The number of citations has been widely used to measure the significance of a paper. However, there is a need in introducing another index to determine superiority or inferiority of papers with the same number of citations. We determine superiority or inferiority of papers by using the ranking based on the number of citations and PageRank. Design/methodology/approach: We show the positive linear correlation between Citation Rank (the ranking of the number of citation) and PageRank. On this basis, we identify high-quality, prestige, emerging, and popular papers. Findings: We found that the high-quality papers belong to the subjects of biochemistry and molecular biology, chemistry, and multidisciplinary sciences. The prestige papers correspond to the subjects of computer science, engineering, and information science. The emerging papers are related to biochemistry and molecular biology, as well as those published in the journal "Cell." The popular papers belong to the subject of multidisciplinary sciences. Research limitations: We analyze the Science Citation Index Expanded (SCIE) from 1981 to 2015 to calculate Citation Rank and PageRank within a citation network consisting of 34,666,719 papers and 591,321,826 citations. Practical implications: Our method is applicable to forecast emerging fields of research subjects in science and helps policymakers to consider science policy. Originality/value: We calculated PageRank for a giant citation network which is extremely larger than the citation networks investigated by previous researchers. [ABSTRACT FROM AUTHOR]

Classifying papers according to the fields of knowledge is critical to clearly understand the dynamics of scientific (sub)fields, their leading questions, and trends. Most studies rely on journal categories defined by popular databases such as WoS or Scopus, but some experts find that those categories may not correctly map the existing subfields nor identify the subfield of a specific article. This study addresses the classification problem using data from each paper (Abstract, Title, Keywords, and the KeyWords Plus) and the help of experts to identify the existing subfields and journals exclusive of each subfield. These "exclusive journals" are critical to obtain, through a pattern detection procedure that uses machine learning techniques (from software NVivo), a list of the frequent terms that are specific to each subfield. With that list of terms and with the help of optimization procedures, we can identify to which subfield each paper most likely belongs. This study can contribute to support scientific policy‐makers, funding, and research institutions—via more accurate academic performance evaluations—, to support editors in their tasks to redefine the scopes of journals, and to support popular databases in their processes of refining categories. [ABSTRACT FROM AUTHOR]

The correction practice of scientific publications is usually used to correct publication errors by issuing correction notices, and it is less explored compared to retraction practice. The aim of this study is to present an overview of correction practice and to explore the citation situation of correction notices in library and information science (LIS) journals, using 720 correction notices in the Web of Science from 2001–2020. Through bibliometrics and content analysis, we found the correcting rate of LIS was relatively low. The main types of corrected errors occurred in authorship, figure or table, references, etc. Most corrected errors were trivial or minor. The citation situation of correction notices was more complex than expected and could be classified into five types. It was relatively rare to cite both the corrected paper and correction notice in a standardized manner. The remaining four types of citation were unreasonable, which could influence citation practice and reduce the citations of corrected papers. We concluded that the appearance of the correction notice had affected the citation of the corrected papers to some extent, and researchers and databases needed to pay attention to this problem. We also provided some suggestions for improving correction practice. [ABSTRACT FROM AUTHOR]

This study analyzed top papers published in the field of Library and Information Science (LIS) published between 2009 and 2019 and included in the Web of Science (WoS) subject category "Information Science & Library Science". Data of the 501 top papers were extracted from the Essential Science Indicators (ESI) database comprising 499 highly cited papers and 16 hot papers in the field. The distributions of document type, language of publication, scientific output, and publication of journals are reported in this paper. The co-authorship network visualization of authors, organizations and countries, co-occurrence network visualization of all keywords are visualized using VOSviewer software. The 501 papers, all written in English language, were from 1,579 authors employed at 680 organizations based in 59 countries/territories. The papers were published in 40 journals in the field. The top 5 core journals ranked based on the impact factor (IF) were MIS Quarterly, Journal of the American Medical Informatics Association, International Journal of Information Management, Journal of the Association for Information Science and Technology, and Information Management. The top 5 organizations were University of Maryland (USA), University of Wolverhampton (UK), Vanderbilt University (USA), Indiana University (USA), and Wuhan University (China). Authors from the following countries contributed the most - USA, People's Republic of China, England, Canada and Netherlands. Based on network map using VOSviewer, there were micro, meso and macro level collaborations based on common interests in a specific topics. Analysis of all keywords showed that the research were distributed into 6 clusters. This study concludes that one important characteristic of top papers is the journal reputation, therefore authors can choose their ideal journal with a high JIF and quartile to publish papers in the English language related to this research field. [ABSTRACT FROM AUTHOR]

Service-Learning (SL) is a powerful methodology to acquire competences and values in Higher Education. However, there is still no widespread use in Information and Computer Science (ICS) degrees where most of the subjects are focused on the development of theoretical and practical contents purely related to technical competences. In this paper, we show the structure of a SL methodology to develop Bachelor's Thesis: 1) definition of proposals considering all the competencies of the Bachelor's Thesis subject and the needs of entities; 2) development of applications using agile methodologies, and 3) assessment of the SL experience from students, entities and professors. We present an experience developed in the 2019/2020 academic year with two entities devoted to disfavoured people. The results show both the high technical and professional quality of the projects and the high satisfaction of entities and students. We hope that the development of applications with the collaboration of non-profit entities allows the acquisition of both specific and transversal competencies on ICS degrees at the same time enhancing the development of useful professional ones.

This work analyses the structure of LIS program mission statements. The programs considered here are all ALA (American Library Association) accredited programs in the United States and Canada. The study employed content analysis through constant comparative analysis to determine the structure of the mission statements, the stakeholders represented in these as well as and the needs the programs satisfy for the different stakeholders. The results point to LIS programs employing symbolic mission statements that do not help to differentiate one program from another. The stakeholders represented were mainly students and external groups, both in interactions with one another.

This summary is about a special issue of the International Journal on Digital Libraries (IJDL) that features selected papers from the 23rd International Conference on Asia-Pacific Digital Libraries (ICADL 2021). ICADL is an annual interdisciplinary conference that connects digital libraries, computer science, and library and information science communities. The special issue includes five papers that have undergone a rigorous review process and cover topics such as improving scientific publication retrieval, multi-label document classification, extracting leaderboards from research papers, and AI-powered peer review systems. The articles offer diverse perspectives and high-quality research within these fields. [Extracted from the article]

This document is a summary of a special issue of the International Journal on Digital Libraries (IJDL) that features selected papers from the 24th International Conference on Asia–Pacific Digital Libraries (ICADL 2022). ICADL is an annual interdisciplinary conference that connects digital library, computer science, and information science communities. The conference was held in Ha Noi, Vietnam, with the theme "From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries." The special issue includes four papers that cover topics such as political opinions, web archives, cultural heritage content, and literature management. The papers underwent a rigorous review process and were selected based on their high quality. The authors hope that readers will find these papers interesting and insightful. [Extracted from the article]

Classic papers are novel facilities of Google scholar. These papers were first developed by Google scholar in May 2017. Classic papers have been considered highly cited papers since last 10 years. Effective authors, institutions, universities, and countries on improving science can be identified by analyzing the papers. Therefore, this study aims to examine characteristics of classic papers of Library and Information Science (LIS). This study will use Scientometrics indicators. The study sample includes LIS classic papers. To gather the data, some databases such as Google scholar, Web of Science, and Scopus are applied. Excel and SPSS applications are used for descriptive and statistical analyses. The study data indicate that Scientometrics journal covers most classic papers on LIS (5 papers). 60% of the papers are written by more than one author. A paper of "Usage Pattern of Collaborating Tagging System" is highly cited paper of LIS with 3051 and 1308 citations on Google scholar and Scopus respectively. Analysis of authors' affiliation shows that American universities and institutions play considerable role in LIS classic papers. The data of statistical tests indicate that there is a positive significant correlation between citations of classic papers of Google scholar, Scopus and Web of Science. [ABSTRACT FROM AUTHOR]

Purpose: This study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor. Design/methodology/approach: Taking SSCI journals in library and information science (LIS) as the research object, the authors first explore the skewness degree of the citation distribution of journal articles. Then, we define the paper citation ratio as the weight of impact factor to modify the journal impact factor for the evaluation of papers, namely the weighted impact factor. The authors further explore the feasibility of the weighted impact factor in evaluating papers. Findings: The research results show that different types of skewness exist in the citation distribution of journal papers. Particularly, 94% of journal paper citations are highly skewed, while the rest are moderately skewed. The weighted impact factor has a closer correlation with the citation frequency of papers than the journal impact factor. It resolves the issue that the journal impact factor tends to exaggerate the influence of low-cited papers in journals with high impact factors or weaken the influence of high-cited papers in journals with low impact factors. Originality/value: The weighted impact factor is constructed based on the skewness of the citation distribution of journal articles. It provides a new method to distinguish the academic influence of different papers published in journals of the same subject or field, then avoids the situation that papers published in the same journal having the same academic impact. [ABSTRACT FROM AUTHOR]

Purpose: In recent years, one can witness a trend in research evaluation to measure the impact on society or attention to research by society (beyond science). We address the following question: can Twitter be meaningfully used for the mapping of public and scientific discourses? Design/methodology/approach: Recently, Haunschild et al. (2019) introduced a new network-oriented approach for using Twitter data in research evaluation. Such a procedure can be used to measure the public discussion around a specific field or topic. In this study, we used all papers published in the Web of Science (WoS, Clarivate Analytics) subject category Information Science & Library Science to explore the publicly discussed topics from the area of library and information science (LIS) in comparison to the topics used by scholars in their publications in this area. Findings: The results show that LIS papers are represented rather well on Twitter. Similar topics appear in the networks of author keywords of all LIS papers, not tweeted LIS papers, and tweeted LIS papers. The networks of the author keywords of all LIS papers and not tweeted LIS papers are most similar to each other. Research limitations: Only papers published since 2011 with DOI were analyzed. Practical implications: Although Twitter data do not seem to be useful for quantitative research evaluation, it seems that Twitter data can be used in a more qualitative way for mapping of public and scientific discourses. Originality/value: This study explores a rather new methodology for comparing public and scientific discourses. [ABSTRACT FROM AUTHOR]

Objectives: Information professionals have supported medical providers, administrators and decision-makers, and guideline creators in the COVID-19 response. Searching COVID-19 literature presented new challenges, including the volume and heterogeneity of literature and the proliferation of new information sources, and exposed existing issues in metadata and publishing. An expert panel developed best practices, including recommendations, elaborations, and examples, for searching during public health emergencies. Methods: Project directors and advisors developed core elements from experience and literature. Experts, identified by affiliation with evidence synthesis groups, COVID-19 search experience, and nomination, responded to an online survey to reach consensus on core elements. Expert participants provided written responses to guiding questions. A synthesis of responses provided the foundation for focus group discussions. A writing group then drafted the best practices into a statement. Experts reviewed the statement prior to dissemination. Results: Twelve information professionals contributed to best practice recommendations on six elements: core resources, search strategies, publication types, transparency and reproducibility, collaboration, and conducting research. Underlying principles across recommendations include timeliness, openness, balance, preparedness, and responsiveness. Conclusions: The authors and experts anticipate the recommendations for searching for evidence during public health emergencies will help information specialists, librarians, evidence synthesis groups, researchers, and decision-makers respond to future public health emergencies, including but not limited to disease outbreaks. The recommendations complement existing guidance by addressing concerns specific to emergency response. The statement is intended as a living document. Future revisions should solicit input from a broader community and reflect conclusions of meta-research on COVID-19 and health emergencies. [ABSTRACT FROM AUTHOR]

Identifies personal transferable skills that employers feel are necessary in the information professions and lacking in graduates of information science programs, including communication skills. The discussion covers the effects of this lack, the need for departments of library and information science to address the problem, and possible methods for teaching such skills. (12 references) (CLB)

Science as a whole is organized into broad fields, and as a consequence, research, resources, students, etc., are also classified, assigned, or invited following a similar structure. Some fields have been established for centuries, and some others are just flourishing. Funding, staff, etc., to support fields are offered if there is some activity on it, commonly measured in terms of the number of published scientific papers. How to find them? There exist well-respected listings where scientific journals are ascribed to one or more knowledge fields. Such lists are human-made, but the complexity begins when a field covers more than one area of knowledge. How to discern if a particular paper is devoted to a field not considered in such lists? In this work, we propose a methodology able to classify the universe of papers into two classes; those belonging to the field of interest, and those that do not. This proposed procedure learns from the title and abstract of papers published in monothematic or "pure" journals. Provided that such journals exist, the procedure could be applied to any field of knowledge. We tested the process with Geographic Information Science. The field has contacts with Computer Science, Mathematics, Cartography, and others, a fact which makes the task very difficult. We also tested our procedure and analyzed its results with three different criteria, illustrating its power and capabilities. Interesting findings were found, where our proposed solution reached similar results as human taggers also similar results compared with state-of-the-art related work. [ABSTRACT FROM AUTHOR]