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New roles of research data infrastructure in research paradigm evolution Journal of Data and Information Science Pub Date : 2024-03-05 Yizhan Li, Lu Dong, Xiaoxiao Fan, Ren Wei, Shijie Guo, Wenzhen Ma, Zexia Li
Research data infrastructures form the cornerstone in both cyber and physical spaces, driving the progression of the data-intensive scientific research paradigm. This opinion paper presents an overview of global research data infrastructure, drawing insights from national roadmaps and strategic documents related to research data infrastructure. It emphasizes the pivotal role of research data infrastructures
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General laws of funding for scientific citations: how citations change in funded and unfunded research between basic and applied sciences Journal of Data and Information Science Pub Date : 2024-02-26 Mario Coccia, Saeed Roshani
Purpose The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences. Design/methodology/approach A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database. Findings The original results reveal general characteristics of
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An explorative study on document type assignment of review articles in Web of Science, Scopus and journals’ websites Journal of Data and Information Science Pub Date : 2024-02-19 Manman Zhu, Xinyue Lu, Fuyou Chen, Liying Yang, Zhesi Shen
Purpose Accurately assigning the document type of review articles in citation index databases like Web of Science(WoS) and Scopus is important. This study aims to investigate the document type assignation of review articles in Web of Science, Scopus and Publisher’s websites on a large scale. Design/methodology/approach 27,616 papers from 160 journals from 10 review journal series indexed in SCI are
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Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020 Journal of Data and Information Science Pub Date : 2024-02-19 Mario Coccia, Saeed Roshani
Purpose The goal of this study is a comparative analysis of the relation between funding (a main driver for scientific research) and citations in papers of Nobel Laureates in physics, chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole. Design/Methodology/Approach This study utilizes a power law model to explore the relationship between research funding and
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A new evolutional model for institutional field knowledge flow network Journal of Data and Information Science Pub Date : 2024-02-05 Jinzhong Guo, Kai Wang, Xueqin Liao, Xiaoling Liu
Purpose This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model (IKM). The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge
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Extended Lorenz majorization and frequencies of distances in an undirected network Journal of Data and Information Science Pub Date : 2024-02-05 Leo Egghe
Purpose To contribute to the study of networks and graphs. Design/methodology/approach We apply standard mathematical thinking. Findings We show that the distance distribution in an undirected network Lorenz majorizes the one of a chain. As a consequence, the average and median distances in any such network are smaller than or equal to those of a chain. Research limitations We restricted our investigations
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Characterizing structure of cross-disciplinary impact of global disciplines: A perspective of the Hierarchy of Science Journal of Data and Information Science Pub Date : 2024-02-05 Ruolan Liu, Jin Mao, Gang Li, Yujie Cao
Purpose Interdisciplinary fields have become the driving force of modern science and a significant source of scientific innovation. However, there is still a paucity of analysis about the essential characteristics of disciplines’ cross-disciplinary impact. Design/methodology/approach In this study, we define cross-disciplinary impact on one discipline as its impact to other disciplines, and refer to
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The Triple Helix of innovation as a double game involving domestic and foreign actors Journal of Data and Information Science Pub Date : 2024-01-25 Eustache Mêgnigbêto
Purpose The collaboration relationships between innovation actors at a geographic level may be considered as grouping two separate layers, the domestic and the foreign. At the level of each layer, the relationships and the actors involved constitute a Triple Helix game. The paper distinguished three levels of analysis: the global grouping together all actors, the domestic grouping together domestic
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A comparison of model choice strategies for logistic regression Journal of Data and Information Science Pub Date : 2024-01-25 Markku Karhunen
Purpose The purpose of this study is to develop and compare model choice strategies in context of logistic regression. Model choice means the choice of the covariates to be included in the model. Design/methodology/approach The study is based on Monte Carlo simulations. The methods are compared in terms of three measures of accuracy: specificity and two kinds of sensitivity. A loss function combining
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Mapping the geography of editors-in-chief Journal of Data and Information Science Pub Date : 2023-12-30 György Csomós
Purpose This study aims to explore the geography of editors-in-chief to demonstrate which countries exercise the highest-level decision-making in scholarly communication. In addition, the study seeks to investigate the potential relationships between the origin and nationality of academic publishers and the geography of editors-in-chief. Design/methodology/approach The analysis involves 11,915 journals
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Dimensionality reduction model based on integer planning for the analysis of key indicators affecting life expectancy Journal of Data and Information Science Pub Date : 2023-12-04 Wei Cui, Zhiqiang Xu, Ren Mu
Purpose Exploring a dimensionality reduction model that can adeptly eliminate outliers and select the appropriate number of clusters is of profound theoretical and practical importance. Additionally, the interpretability of these models presents a persistent challenge. Design/methodology/approach This paper proposes two innovative dimensionality reduction models based on integer programming (DRMBIP)
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The need to develop tailored tools for improving the quality of thematic bibliometric analyses: Evidence from papers published in Sustainability and Scientometrics Journal of Data and Information Science Pub Date : 2023-09-22 Alvaro Cabezas-Clavijo, Yusnelkis Milanés-Guisado, Ruben Alba-Ruiz, Ángel M. Delgado-Vázquez
Purpose 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. Design/methodology/approach The study identifies the need for developing
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The notion of dominant terminology in bibliometric research Journal of Data and Information Science Pub Date : 2023-09-13 Yves Fassin, Ronald Rousseau
In this opinion paper, we introduce the expressions of dominant terminology and dominant term in the quantitative studies of science in analogy to the notion of dominant design in product development and innovation.
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Differences between journal and conference in computer science: a bibliometric view based on Bayesian network Journal of Data and Information Science Pub Date : 2023-08-25 Mingyue Sun, Mingliang Yue, Tingcan Ma
Purpose This paper aims to investigate the differences between conference papers and journal papers in the field of computer science based on Bayesian network. Design/methodology/approach This paper investigated the differences between conference papers and journal papers in the field of computer science based on Bayesian network, a knowledge-representative framework that can model relationships among
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Editorial board publication strategy and acceptance rates in Turkish national journals Journal of Data and Information Science Pub Date : 2023-08-25 Lokman Tutuncu
Purpose This study takes advantage of newly released journal metrics to investigate whether local journals with more qualified boards have lower acceptance rates, based on data from 219 Turkish national journals and 2,367 editorial board members. Design/methodology/approach This study argues that journal editors can signal their scholarly quality by publishing in reputable journals. Conversely, editors
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Perspectives from a publishing ethics and research integrity team for required improvements Journal of Data and Information Science Pub Date : 2023-07-21 Sabina Alam, Laura Wilson
It is imperative that all stakeholders within the research ecosystem take responsibility to improve research integrity and reliability of published research. Based on the unique experiences of a specialist publishing ethics and research integrity team within a major publisher, this article provides insights into the observed trends of misconduct and how those have evolved over time, and addresses key
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An author credit allocation method with improved distinguishability and robustness Journal of Data and Information Science Pub Date : 2023-06-24 Yang Li, Tao Jia
Purpose The purpose of this study is to propose an improved credit allocation method that makes the leading author of the paper more distinguishable and makes the deification more robust under malicious manipulations. Design/methodology/approach We utilize a modified Sigmoid function to handle the fat-tail distributed citation counts. We also remove the target paper in calculating the contribution
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Multimodal sentiment analysis for social media contents during public emergencies Journal of Data and Information Science Pub Date : 2023-06-13 Tao Fan, Hao Wang, Peng Wu, Chen Ling, Milad Taleby Ahvanooey
Purpose Nowadays, public opinions during public emergencies involve not only textual contents but also contain images. However, the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis, lacking the combination of multimodal contents. In this paper, we propose to combine texts and images generated in the social media to perform sentiment
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Build neural network models to identify and correct news headlines exaggerating obesity-related scientific findings Journal of Data and Information Science Pub Date : 2023-06-07 Ruopeng An, Quinlan Batcheller, Junjie Wang, Yuyi Yang
Purpose Media exaggerations of health research may confuse readers’ understanding, erode public trust in science and medicine, and cause disease mismanagement. This study built artificial intelligence (AI) models to automatically identify and correct news headlines exaggerating obesity-related research findings. Design/methodology/approach We searched popular digital media outlets to collect 523 headlines
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Global trends in international research collaboration, 1980-2021① Journal of Data and Information Science Pub Date : 2023-06-07 Dag W. Aksnes, Gunnar Sivertsen
Purpose The aim of this study is to analyze the evolution of international research collaboration from 1980 to 2021. The study examines the main global patterns as well as those specific to individual countries, country groups, and different areas of research. Design/methodology/approach The study is based on the Web of Science Core collection database. More than 50 million publications are analyzed
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Can first or last name uniqueness help to identify diaspora researchers from any country? Journal of Data and Information Science Pub Date : 2023-06-07 Mike Thelwall
Purpose Diaspora researchers work in one country but have ancestral origins in another, either through moves during a research career (mobile diaspora researchers) or by starting research in the target country (embedded diaspora researchers). Whilst mobile researchers might be tracked through affiliation changes in bibliometric databases, embedded researchers cannot. This article reports an evidence-based
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Evaluating grant proposals: lessons from using metrics as screening device Journal of Data and Information Science Pub Date : 2023-05-04 Katerina Guba, Alexey Zheleznov, Elena Chechik
Purpose This study examines the effects of using publication-based metrics for the initial screening in the application process for a project leader. The key questions are whether formal policy affects the allocation of funds to researchers with a better publication record and how the previous academic performance of principal investigators is related to future project results. Design/methodology/approach
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International visibility of Armenian domestic journals: the role of scientific diaspora Journal of Data and Information Science Pub Date : 2023-05-04 Edita Gzoyan, Aram Mirzoyan, Anush Sargsyan, Mariam Yeghikyan, Domenico A. Maisano, Shushanik Sargsyan
Purpose Nearly 122 scientific journals are currently being published in Armenia—of which only six are indexed by WoS and/or Scopus databases. The majority of the national journals are published in the Armenian language, solely possessing abstracts written in English, although there are also English-language and multi-language journals with articles not only in Armenian but also in other foreign languages
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Regression discontinuity design and its applications to Science of Science: A survey Journal of Data and Information Science Pub Date : 2023-04-22 Meiling Li, Yang Zhang, Yang Wang
Purpose With the availability of large-scale scholarly datasets, scientists from various domains hope to understand the underlying mechanisms behind science, forming a vibrant area of inquiry in the emerging “science of science” field. As the results from the science of science often has strong policy implications, understanding the causal relationships between variables becomes prominent. However
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Is big team research fair in national research assessments? The case of the UK Research Excellence Framework 2021 Journal of Data and Information Science Pub Date : 2023-03-05 Mike Thelwall, Kayvan Kousha, Meiko Makita, Mahshid Abdoli, Emma Stuart, Paul Wilson, Jonathan Levitt
Collaborative research causes problems for research assessments because of the difficulty in fairly crediting its authors. Whilst splitting the rewards for an article amongst its authors has the greatest surface-level fairness, many important evaluations assign full credit to each author, irrespective of team size. The underlying rationales for this are labour reduction and the need to incentivise
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Causal inference using regression-based statistical control: Confusion in Econometrics Journal of Data and Information Science Pub Date : 2023-03-05 Fan Chao, Guang Yu
Regression is a widely used econometric tool in research. In observational studies, based on a number of assumptions, regression-based statistical control methods attempt to analyze the causation between treatment and outcome by adding control variables. However, this approach may not produce reliable estimates of causal effects. In addition to the shortcomings of the method, this lack of confidence
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Practical operation and theoretical basis of difference-in-difference regression in science of science: The comparative trial on the scientific performance of Nobel laureates versus their coauthors Journal of Data and Information Science Pub Date : 2023-03-05 Yurui Huang, Chaolin Tian, Yifang Ma
Purpose In recent decades, with the availability of large-scale scientific corpus datasets, difference-in-difference (DID) is increasingly used in the science of science and bibliometrics studies. DID method outputs the unbiased estimation on condition that several hypotheses hold, especially the common trend assumption. In this paper, we gave a systematic demonstration of DID in the science of science
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Peculiarities of gender disambiguation and ordering of non-English authors’ names for Economic papers beyond core databases① Journal of Data and Information Science Pub Date : 2022-12-06 Olesya Mryglod, Serhii Nazarovets, Serhiy Kozmenko
Purpose To supplement the quantitative portrait of Ukrainian Economics discipline with the results of gender and author ordering analysis at the level of individual authors, special methods of working with bibliographic data with a predominant share of non-English authors are used. The properties of gender mixing, the likelihood of male and female authors occupying the first position in the authorship
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Subject Area Risk Assessment of Four Hungarian Universities with a View to the QS University Rankings by Subject Journal of Data and Information Science Pub Date : 2022-11-12 Péter Sasvári, Anna Urbanovics
Purpose The aim of our paper is to investigate the role of a mentor leading a research team in the overall scientific performance of an academic institution and the possible risks of their departure with a special attention to their publication output. Design/methodology/approach By using SciVal subject area data, we composed a formula describing the level of vulnerability of any given university in
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Confidence Intervals for Relative Intensity of Collaboration (RIC) Indicators Journal of Data and Information Science Pub Date : 2022-10-19 Joel Emanuel Fuchs, Lawrence Smolinsky, Ronald Rousseau
Purpose We aim to extend our investigations related to the Relative Intensity of Collaboration (RIC) indicator, by constructing a confidence interval for the obtained values. Design/methodology/approach We use Mantel-Haenszel statistics as applied recently by Smolinsky, Klingenberg, and Marx. Findings We obtain confidence intervals for the RIC indicator Research limitations It is not obvious that data
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What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature Journal of Data and Information Science Pub Date : 2022-09-08 Brady Lund, Ting Wang
This paper reviews literature pertaining to the development of data science as a discipline, current issues with data bias and ethics, and the role that the discipline of information science may play in addressing these concerns. Information science research and researchers have much to offer for data science, owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral
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A Use Case of Patent Classification Using Deep Learning with Transfer Learning Journal of Data and Information Science Pub Date : 2022-08-12 Roberto Henriques, Adria Ferreira, Mauro Castelli
Purpose Patent classification is one of the areas in Intellectual Property Analytics (IPA), and a growing use case since the number of patent applications has been increasing worldwide. We propose using machine learning algorithms to classify Portuguese patents and evaluate the performance of transfer learning methodologies to solve this task. Design/methodology/approach We applied three different
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Implications of Publication Requirements for the Research Output of Ukrainian Academics in Scopus in 1999–2019 Journal of Data and Information Science Pub Date : 2022-08-12 Myroslava Hladchenko
Purpose This article explores the implications of publication requirements for the research output of Ukrainian academics in Scopus in 1999–2019. As such it contributes to the existing body of knowledge on quantitative and qualitative effects of research evaluation policies. Design/methodology/approach Three metrics were chosen to analyse the implications of publication requirements for the quality
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A Morphology-Driven Method for Measuring Technology Complementarity: Empirical Study Involving Alzheimer's Disease Journal of Data and Information Science Pub Date : 2022-08-12 Xuefeng Wang, Rongrong Li, Yuqin Liu, Ming Lei
Purpose Measuring the exact technology complementarity between different institutions is necessary to obtain complementary technology resources for R&D cooperation. Design/methodology/approach This study constructs a morphology-driven method for measuring technology complementarity, taking medical field as an example. First, we calculate semantic similarities between subjects (S and S) and action-objects
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Convergence of Impact Measures and Impact Bundles Journal of Data and Information Science Pub Date : 2022-07-16 Leo Egghe
Purpose A new point of view in the study of impact is introduced. Design/methodology/approach Using fundamental theorems in real analysis we study the convergence of well-known impact measures. Findings We show that pointwise convergence is maintained by all well-known impact bundles (such as the h-, g-, and R-bundle) and that the μ-bundle even maintains uniform convergence. Based on these results
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Bibliometrics Is Valuable Science. Why Do Some Journals Seem to Oppose It? Journal of Data and Information Science Pub Date : 2022-04-22 Brady Lund
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I Don’t Peer-Review for Non-Open Journals, and Neither Should You Journal of Data and Information Science Pub Date : 2022-04-01 Michael P. Taylor
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Contribution of the Open Access Modality to the Impact of Hybrid Journals Controlling by Field and Time Effects Journal of Data and Information Science Pub Date : 2022-04-01 Pablo Dorta-González,María Isabel Dorta-González
Abstract Purpose Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain. Thus, the objective of this work is to analyze the contribution of the Open Access (OA) modality to the impact of hybrid journals. Design/methodology/approach The “research articles” in the year 2017 from 200 hybrid journals in four subject areas, and the citations received
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Learning Context-based Embeddings for Knowledge Graph Completion Journal of Data and Information Science Pub Date : 2022-04-01 Fei Pu,Zhongwei Zhang,Yan Feng,Bailin Yang
Abstract Purpose Due to the incompleteness nature of knowledge graphs (KGs), the task of predicting missing links between entities becomes important. Many previous approaches are static, this posed a notable problem that all meanings of a polysemous entity share one embedding vector. This study aims to propose a polysemous embedding approach, named KG embedding under relational contexts (ContE for
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I’m Nervous about Sharing This Secret with You: Youtube Influencers Generate Strong Parasocial Interactions by Discussing Personal Issues Journal of Data and Information Science Pub Date : 2022-04-01 Mike Thelwall,Emma Stuart,Amalia Mas-Bleda,Meiko Makita,Mahshid Abdoli
Abstract Purpose Performers may generate loyalty partly through eliciting illusory personal connections with their audience, parasocial relationships (PSRs), and individual illusory exchanges, parasocial interactions (PSIs). On social media, semi-PSIs are real but imbalanced exchanges with audiences, including through comments on influencers’ videos, and strong semi-PSIs are those that occur within
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Fighting Against Academic Misconduct: What Can Scientometricians Do? Journal of Data and Information Science Pub Date : 2022-04-01 Sichao Tong,Zhesi Shen,Tian-Yuan Huang,Liying Yang
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The Three-Step Workflow: A Pragmatic Approach to Allocating Academic Hospitals’ Affiliations for Bibliometric Purposes Journal of Data and Information Science Pub Date : 2022-02-01 Andrea Reyes Elizondo,Clara Calero-Medina,Martijn S. Visser
Abstract Purpose A key question when ranking universities is whether or not to allocate the publication output of affiliated hospitals to universities. This paper presents a method for classifying the varying degrees of interdependency between academic hospitals and universities in the context of the Leiden Ranking. Design/methodology/approach Hospital nomenclatures vary worldwide to denote some form
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Academic Collaborator Recommendation Based on Attributed Network Embedding Journal of Data and Information Science Pub Date : 2022-02-01 Ouxia Du,Ya Li
Abstract Purpose Based on real-world academic data, this study aims to use network embedding technology to mining academic relationships, and investigate the effectiveness of the proposed embedding model on academic collaborator recommendation tasks. Design/methodology/approach We propose an academic collaborator recommendation model based on attributed network embedding (ACR-ANE), which can get enhanced
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Progress and Knowledge Transfer from Science to Technology in the Research Frontier of CRISPR Based on the LDA Model Journal of Data and Information Science Pub Date : 2022-02-01 Yushuang Lyu,Muqi Yin,Fangjie Xi,Xiaojun Hu
Abstract Purpose This study explores the underlying research topics regarding CRISPR based on the LDA model and figures out trends in knowledge transfer from science to technology in this area over the latest 10 years. Design/methodology/approach We collected publications on CRISPR between 2011 and 2020 from the Web of Science, and traced all the patents citing them from lens.org. 15,904 articles and
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Parameterless Pruning Algorithms for Similarity-Weight Network and Its Application in Extracting the Backbone of Global Value Chain Journal of Data and Information Science Pub Date : 2021-12-11 Lizhi Xing,Yu Han
Abstract Purpose With the availability and utilization of Inter-Country Input-Output (ICIO) tables, it is possible to construct quantitative indices to assess its impact on the Global Value Chain (GVC). For the sake of visualization, ICIO networks with tremendous low- weight edges are too dense to show the substantial structure. These redundant edges, inevitably make the network data full of noise
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Public Reaction to Scientific Research via Twitter Sentiment Prediction Journal of Data and Information Science Pub Date : 2021-12-11 Murtuza Shahzad,Hamed Alhoori
Abstract Purpose Social media users share their ideas, thoughts, and emotions with other users. However, it is not clear how online users would respond to new research outcomes. This study aims to predict the nature of the emotions expressed by Twitter users toward scientific publications. Additionally, we investigate what features of the research articles help in such prediction. Identifying the sentiments
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The Roles of Female Involvement and Risk Aversion in Open Access Publishing Patterns in Vietnamese Social Sciences and Humanities Journal of Data and Information Science Pub Date : 2021-12-11 Minh-Hoang Nguyen,Huyen Thanh Thanh Nguyen,Manh-Toan Ho,Tam-Tri Le,Quan-Hoang Vuong
Abstract Purpose The open-access (OA) publishing model can help improve researchers’ outreach, thanks to its accessibility and visibility to the public. Therefore, the presentation of female researchers can benefit from the OA publishing model. Despite that, little is known about how gender affects OA practices. Thus, the current study explores the effects of female involvement and risk aversion on
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Feature and Tendency of Technology Transfer in Z-Park Patent Cooperation Network: From the Perspective of Global Optimal Path Journal of Data and Information Science Pub Date : 2021-11-01 Jun Guan,Jingying Xu,Yu Han,Dawei Wang,Lizhi Xing
Abstract Purpose This study aims to provide a new framework for analyzing the path of technology diffusion in the innovation network at the regional level and industrial level respectively, which is conducive to the integration of innovation resources, the coordinated development of innovative subjects, and the improvement of innovation abilities. Design/methodology/approach Based on the Z-Park patent
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Scientific Value Weights more than Being Open or Toll Access: An analysis of the OA advantage in Nature and Science Journal of Data and Information Science Pub Date : 2021-09-26 Howell Y. Wang,Shelia X. Wei,Cong Cao,Xianwen Wang,Fred Y. Ye
Abstract Purpose We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries. Design/methodology/approach We design the indicators, hot-degree, and R-index to indicate a topic OA or TA advantages. First, according to the OA classification of the Web of Science (WoS), we collect data from the WoS by downloading OA and TA articles, letters, and reviews published
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A Topic Detection Method Based on Word-attention Networks Journal of Data and Information Science Pub Date : 2021-08-18 Zheng Xie
Abstract Purpose We proposed a method to represent scientific papers by a complex network, which combines the approaches of neural and complex networks. Design/methodology/approach Its novelty is representing a paper by a word branch, which carries the sequential structure of words in sentences. The branches are generated by the attention mechanism in deep learning models. We connected those branches
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How Has Covid-19 Affected Published Academic Research? A Content Analysis of Journal Articles Mentioning the Virus Journal of Data and Information Science Pub Date : 2021-08-18 Mike Thelwall,Saheeda Thelwall
Abstract Purpose Methods to tackle Covid-19 have been developed by a wave of biomedical research but the pandemic has also influenced many aspects of society, generating a need for research into its consequences, and potentially changing the way existing topics are investigated. This article investigates the nature of this influence on the wider academic research mission. Design/methodology/approach
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Substantiality: A Construct Indicating Research Excellence to Measure University Research Performance Journal of Data and Information Science Pub Date : 2021-07-25 Masashi Shirabe,Amane Koizumi
Abstract Purpose The adequacy of research performance of universities or research institutes have often been evaluated and understood in two axes: “quantity” (i.e. size or volume) and “quality” (i.e. what we define here as a measure of excellence that is considered theoretically independent of size or volume, such as clarity in diamond grading). The purpose of this article is, however, to introduce
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New Indicators of the Technological Impact of Scientific Production Journal of Data and Information Science Pub Date : 2021-06-24 Vicente P. Guerrero-Bote,Henk F. Moed,Félix Moya-Anegón
Abstract Purpose Building upon pioneering work by Francis Narin and others, a new methodological approach to assessing the technological impact of scientific research is presented. Design/methodology/approach It is based on the analysis of citations made in patent families included in the PATSTAT database that is to scientific papers indexed in Scopus. Findings An advanced citation matching procedure
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Embedding-based Detection and Extraction of Research Topics from Academic Documents Using Deep Clustering Journal of Data and Information Science Pub Date : 2021-06-01 Sahand Vahidnia,Alireza Abbasi,Hussein A. Abbass
Abstract Purpose Detection of research fields or topics and understanding the dynamics help the scientific community in their decisions regarding the establishment of scientific fields. This also helps in having a better collaboration with governments and businesses. This study aims to investigate the development of research fields over time, translating it into a topic detection problem. Design/methodology/approach
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Extraction and Evaluation of Knowledge Entities from Scientific Documents Journal of Data and Information Science Pub Date : 2021-06-01 Chengzhi Zhang,Philipp Mayr,Wei Lu,Yi Zhang
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A New Citation Recommendation Strategy Based on Term Functions in Related Studies Section Journal of Data and Information Science Pub Date : 2021-05-09 Haihua Chen
Abstract Purpose Researchers frequently encounter the following problems when writing scientific articles: (1) Selecting appropriate citations to support the research idea is challenging. (2) The literature review is not conducted extensively, which leads to working on a research problem that others have well addressed. The study focuses on citation recommendation in the related studies section by
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Sentence, Phrase, and Triple Annotations to Build a Knowledge Graph of Natural Language Processing Contributions—A Trial Dataset Journal of Data and Information Science Pub Date : 2021-05-09 Jennifer D’Souza,Sören Auer
Abstract Purpose This work aims to normalize the NlpContributions scheme (henceforward, NlpContributionGraph) to structure, directly from article sentences, the contributions information in Natural Language Processing (NLP) scholarly articles via a two-stage annotation methodology: 1) pilot stage—to define the scheme (described in prior work); and 2) adjudication stage—to normalize the graphing model
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RDFAdaptor: Efficient ETL Plugins for RDF Data Process Journal of Data and Information Science Pub Date : 2021-04-14 Jiao Li,Guojian Xian,Ruixue Zhao,Yongwen Huang,Yuantao Kou,Tingting Luo,Tan Sun
Abstract Purpose The interdisciplinary nature and rapid development of the Semantic Web led to the mass publication of RDF data in a large number of widely accepted serialization formats, thus developing out the necessity for RDF data processing with specific purposes. The paper reports on an assessment of chief RDF data endpoint challenges and introduces the RDF Adaptor, a set of plugins for RDF data
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Why Open Government Data? The Case of a Swedish Municipality Journal of Data and Information Science Pub Date : 2021-01-27 Koraljka Golub, Arwid Lund
Abstract Purpose The purpose of this exploratory study is to provide modern local governments with potential use cases for their open data, in order to help inform related future policies and decision-making. The concrete context was that of the Växjö municipality located in southeastern Sweden. Design/methodology/approach The methodology was two-fold: 1) a survey of potential end users (n=151) from
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Government Data Openness and Coverage. How do They Affect Trust in European Countries? Journal of Data and Information Science Pub Date : 2021-01-27 Nicolás Gonzálvez-Gallego, Laura Nieto-Torrejón
Abstract Purpose This paper aims to assess if the extent of openness and the coverage of data sets released by European governments have a significant impact on citizen trust in public institutions. Design/methodology/approach Data for openness and coverage have been collected from the Open Data Inventory 2018 (ODIN), by Open Data Watch; institutional trust is built up as a formative construct based