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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]

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]

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]

With the wide application of keyphrases in many Information Retrieval (IR) and Natural Language Processing (NLP) tasks, automatic keyphrase prediction has been emerging. However, these statistically important phrases are contributing increasingly less to the related tasks because the end‐to‐end learning mechanism enables models to learn the important semantic information of the text directly. Similarly, keyphrases are of little help for readers to quickly grasp the paper's main idea because the relationship between the keyphrase and the paper is not explicit to readers. Therefore, we propose to generate keyphrases with specific functions for readers to bridge the semantic gap between them and the information producers, and verify the effectiveness of the keyphrase function for assisting users' comprehension with a user experiment. A controllable keyphrase generation framework (the CKPG) that uses the keyphrase function as a control code to generate categorized keyphrases is proposed and implemented based on Transformer, BART, and T5, respectively. For the Computer Science domain, the Macro‐avgs of P@5, R@5, and F1@5 on the Paper with Code dataset are up to 0.680, 0.535, and 0.558, respectively. Our experimental results indicate the effectiveness of the CKPG models. [ABSTRACT FROM AUTHOR]

Academic research often draws on multiple funding sources. This paper investigates whether complementarity or substitutability emerges when different types of funding are used. Scholars have examined this phenomenon at the university and scientist levels, but not at the publication level. This gap is significant since acknowledgement sections in scientific papers indicate publications are often supported by multiple funding sources. To address this gap, we examine the extent to which different funding types are jointly used in publications, and to what extent certain combinations of funding are associated with higher academic impact (citation count). We focus on three types of funding accessed by UK‐based researchers: national, international, and industry. The analysis builds on data extracted from all UK cancer‐related publications in 2011, thus providing a 10‐year citation window. Findings indicate that, although there is complementarity between national and international funding in terms of their co‐occurrence (where these are acknowledged in the same publication), when we evaluate funding complementarity in relation to academic impact (we employ the supermodularity framework), we found no evidence of such a relationship. Rather, our results suggest substitutability between national and international funding. We also observe substitutability between international and industry funding. [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]

Each section header of an article has its distinct communicative function. Citations from distinct sections may be different regarding citing motivation. In this paper, we grouped section headers with similar functions as a structural function and defined the distribution of citations from structural functions for a paper as its citation structure. We aim to explore the relationship between citation structure and the future impact of a publication and disclose the relative importance among citations from different structural functions. Specifically, we proposed two citation counting methods and a citation life cycle identification method, by which the regression data were built. Subsequently, we employed a ridge regression model to predict the future impact of the paper and analyzed the relative weights of regressors. Based on documents collected from the Association for Computational Linguistics Anthology website, our empirical experiments disclosed that functional structure features improve the prediction accuracy of citation count prediction and that there exist differences among citations from different structural functions. Specifically, at the early stage of citation lifetime, citations from Introduction and Method are particularly important for perceiving future impact of papers, and citations from Result and Conclusion are also vital. However, early accumulation of citations from the Background seems less important. [ABSTRACT FROM AUTHOR]

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT‐based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top‐K main paths extracted from various time slices of semantic citation network. In addition, a three‐way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics‐agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas. [ABSTRACT FROM AUTHOR]

In this opinion paper, we frame a discussion on paradigm shift(s) in the field of information. We believe that in this astonishing historical moment of new directions and new opportunities both the existing paradigms and conceptual models in the field of information can benefit from re‐examination to stay current with the times. We propose a framework articulating key narratives associated with the why, what, how, and who dimensions to discuss paradigm shift(s). The purpose of this opinion paper is to initiate dialogues on ground‐breaking ideas and innovative solutions as well as support research that addresses contemporary challenges in the field of information. [ABSTRACT FROM AUTHOR]

Nursing Sciences are at a moment of paradigmatic transition. The aim of this paper is to reflect on the new epistemological paradigms of nursing science from a critical approach. In this paper, we identified and analysed some new research lines and trends which anticipate the reorganization of nursing sciences and the paradigms emerging from nursing care: biotechnology-centred knowledge; the interface between nursing knowledge and new information technologies; body care centred knowledge; the human body as a cyborg body; and the rediscovery of an aesthetic knowledge in nursing care. [ABSTRACT FROM AUTHOR]

In this paper we propose a method for the reciprocal use of knowledge between association rule extraction (a technique from data mining) and HMM-based information extraction. Association rule extraction is a method that is generally applied to structured data and is either inefficient or intractable when applied to data that lacks an accurate information schema. In this paper we use HMM-based information extraction to automatically recognize the attributes of each word in a set of textual data and assign tags in order to structure this data. In addition, we use the degree of association between words seen in the association rules extracted from the structured data to weight the HMM parameters in order to improve the recognition accuracy of the information extraction procedure and allow knowledge to be reciprocally shared between the data mining and information extraction procedures. Besides this we propose a data mining method that uses representative schema patterns found in different types of semistructured data such as tagged or BibTeX data using schema discovery methods. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(7): 51–60, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20256 [ABSTRACT FROM AUTHOR]

In-text frequency-weighted citation counting has been seen as a particularly promising solution to the well-known problem of citation analysis that it treats all citations equally, be they crucial to the citing paper or perfunctory. But what is a good weighting scheme? We compare 12 different in-text citation frequency-weighting schemes in the field of library and information science (LIS) and explore author citation impact patterns based on their performance in these schemes. Our results show that the ranks of authors vary widely with different weighting schemes that favor or are biased against common citation impact patterns-substantiated, applied, or noted. These variations separate LIS authors quite clearly into groups with these impact patterns. With consensus rank limits, the hard upper and lower bounds for reasonable author ranks that they provide suggest that author citation ranks may be subject to something like an uncertainty principle. [ABSTRACT FROM AUTHOR]

Instrument validation is a critical step that researchers should employ in order to ensure the generation of scientifically valid knowledge. Without it, the basis of research findings and the generalization of such are threatened. This is especially true in the social sciences, a discipline in which the majority of published articles utilize subjective instruments in the collection of data. Consequently, instrument validation has increasingly become common practice in the social sciences, yet implementation of this practice differs greatly among the social-science disciplines. The assessment of instrument validation undertaken in this study attempts to provide guidance for reviewers, editors, authors, and readers, by offering various techniques of validity and analyzing the quality of a set of psychometric journal articles. In this research, six attributes of instrument validation areas are identified as validation protocol. The Journal of the American Society for Information Science and Technology (JASIST), which is widely recognized as a leading journal in the field of information science, was selected for examination to determine how well a set of research articles ranked in meeting instrument-validation protocol. Findings show that while researchers are becoming increasingly attentive to certain validation issues, standards on validation processes and reporting might prove helpful. This paper identifies areas for improvement in the reporting of validity measures and offers ways for researchers to implement them. [ABSTRACT FROM AUTHOR]

A brief communication appearing in this journal ranked UK-based LIS and (some) IR academics by their h-index using data derived from the Thomson ISI Web of Science™ (WoS). In this brief communication, the same academics were re-ranked, using other popular citation databases. It was found that for academics who publish more in computer science forums, their h was significantly different due to highly cited papers missed by WoS; consequently, their rank changed substantially. The study was widened to a broader set of UK-based LIS and IR academics in which results showed similar statistically significant differences. A variant of h, hmx, was introduced that allowed a ranking of the academics using all citation databases together. [ABSTRACT FROM AUTHOR]

In May 2000, the Board of Directors of the American Society for Information Science (ASIS) changed the name of the association by adding the words, “and Technology” (&T). Today this change may be considered minor, but for many involved at the time—it was a change that had purpose and meaning. A study was initiated to trace the society's transition toward a professional association more inclusive of practitioners and applied research. The study was conducted in two stages, using quantitative and qualitative methods. Stage 1 compared the research published in the conference proceedings both prior to and following the society's name change. Stage 2 built upon the assumption that a professional association is a reflection of its membership. The Stage 1 results offer both an aggregate and a comparative view of the papers accepted for and presented at the annual conference. The results suggest that as an association of researchers, the society may be moving toward a renewed focus on practical and applied information. The Stage 2 results suggest that some ASIS&T members welcome the increased focus on technology, applied research, and the topics of interest to practitioners. Others view the changes as negative, perhaps even undermining the value of ASIS. The practical implications suggest that an annual conference can be an association's most important branding opportunity. It should reflect the interests of its membership as well as attract new members. A clear vision, supported by the membership, will guide the activities of the society and, in turn, will effectively serve its members professional needs. [ABSTRACT FROM AUTHOR]

Recently compact cryptosystems, incorporating high speeds and accompanied by the development of information networks, have provided the missing technology needed to make secure communications a reality. DES, FEAL, and Multi2 are all involution-type secret-key cryptosystems which are widely used due to their simplicity. On the other hand, with the popularity of these cryptotogic algorithms has come also an increase in research on cryptologic attacks, particularly the method of differential cryptanalysis introduced by Biham and Shamir, a recently developed general-purpose chosen plaintext method of attacking involution-type cryptosystems. In this paper, we first summarize the statistical attack of Gilbert and Chassé, which is based on the method of differential cryptanalysis, and estimate the attack time and the number of plain texts necessary for their attack. In addition, we propose a new technique which enhances the efficiency of this attacking method. This technique, by using in its attack only a subsequence of the generated dihertext sequence which satisfies a specific condition, produces a substantial reduction in the attack time. Also, we demonstrate the possibility of using this method as a real-time chosen-plaintext attack on the Multi2 cryptosystem with up to 12 rounds. [ABSTRACT FROM AUTHOR]

The article presents information related to the May 2004 issue of the "Journal of the American Society for Information Science and Technology." Marcia Lei Zeng and Lois Mai Chan review the current work in facilitating cross indexing system searching using three categories of the digital record organizational system environment—term lists, classifications, and relational vocabularies. Padmini Srinivasan has created algorithms for text mining utilizing the Swanson-Smalheiser hypothesis generating framework which, in the past, has required considerable manual processing. Massimo Melucci wants to generate, without manual intervention, hyperlinks between pages of digital textbooks that allow useful reader navigation. Peter Vinkler notes that if within a set of journals the number of citations obtained and the number of references given are identical, then the set's Garfield Impact factor is the same as the mean chance for citedness of the journal papers. The Garfield Impact factor measures the relative contribution of a journal to the total impact of journals in the field and is shown to be equivalent to a measure specifically designed to represent this relative contribution.