COLLNET Journal of Scientometrics and Information Management最新文献

{"title":"Human and algorithmic decision-making in the personnel selection process: A comparative bibliometric on bias","authors":"Humberta Karinne Da Conceição Santos Silva, L. Vasconcellos","doi":"10.47974/cjsim-2022-0063","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0063","url":null,"abstract":"This article examines, with bibliometrics, the publication on bias in organizations’ personnel selection processes, whether they use automated decision-making systems or human-made decisions. While human bias is dynamic, restricted, mutate, and easier to determine the source; algorithmic bias is large-scale, static, and unpredictable. Despite the apparent discrepancy, there is a symbiotic relationship between those two, but somehow only one of them is getting any attention regarding the consequences of fairness on personnel selection and how this influences organizational diversity. So, looking for a better understanding of organizational behaviour, we conduct a bibliometric review to mappings the relations of these two. Here we reviewed 55 articles from the Web of Science Core Collection, from the earliest research published in 1979 to 2021. Only papers of the document type “article” was considered. The tool used for bibliometric data analysis were bibliometrix packages from the RStudio system version 3.6.3. According to our review, the number of studies on the subject is still tiny, and most of them were conducted under controlled conditions without considering the error agent of an organizational environment such as time, organizational culture, and the emotions of the recruiter; this makes it impossible to develop practices to avoid discrimination in these spaces. Concerning the theme, studies on human bias are the most common, with a focus on gender bias, and have recently adopted diversity. Hardly studies on algorithm decision-making consider the process’s fairness as a topic for investigation. However, neither study demonstrates a correlation or systematic approach between them. More interdisciplinary and empirical research should be the focus of future studies.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping global research on expert systems","authors":"Bisma Bashir, Fayaz Ahmad Loan","doi":"10.47974/cjsim-2021-0103","DOIUrl":"https://doi.org/10.47974/cjsim-2021-0103","url":null,"abstract":"Purpose: The purpose of the study is to conduct a scientometric analysis of expert systems literature indexed in the Science Citation Index Expanded (SCIE) of the Web of Science database for a period of ten years (2011-2020). Design/Methodology: The study collected data from the Science Citation Index Expanded (SCIE) of the Web of Science (WoS) database from 2011-2020. The synonymous, broader and related terms of Expert Systems were selected from the Dewey Decimal Classification Scheme and Sears List of Subject Headings. A string of these terms was employed to retrieve data in the advanced search mode of the database. The harvested data was analyzed using scientometric techniques. Besides, the Microsoft Excel and VOSviewer software were used to represent and map the research productivity on expert systems. Findings: The results indicated inconsistent fluctuations in the annual number of publications from 396 in 2011 to 463 in 2020 and a decline in the number of citations from 8344 in 2011 to 520 in 2020. Further, it is divulged that China, the USA, and Spain are the three top countries contributing to expert system research published 16.36%, 14.96%, and 8.95% of literature respectively. While analysing institutional performance, the results revealed that most of the institutions are from China (6), followed by Iran (4), Spain (3) and India (2) /Malaysia (2) respectively. Further, by clustering the network map for keywords co-occurrence, it was found that expert systems, fuzzy logic, knowledge-based systems, machine learning, and artificial intelligence are the most common keywords and hence the hot topics of research in the area. Practical implications: The findings of the study may help researchers, information scientists and technologists to identify the research progress in the field of expert systems. Besides, it will help librarians to know the hot topics of research, prominent publications and prolific authors in expert systems. This will be helpful in the collection development of expert systems and artificial intelligence in libraries and information centres. Research limitations: The database studied for the work does not represent the total literary output available on expert systems as data in other databases like Scopus, Compendex, IEEE Xplore, arXiv, etc. haven’t been harvested. Originality/Value: The study is based on current literature on expert systems and will highlight new research trends in the said field.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research trends in the field of natural language processing : A scientometric study based on global publications during 2001-2020","authors":"B. Gupta, S. Dhawan, G. M. Mamdapur","doi":"10.47974/cjsim-2022-0023","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0023","url":null,"abstract":"The study provides a quantitative and qualitative description of global research in “Natural Language Processing” ( NLP) using bibliometric methods. The analysis is based on publications data sourced from Scopus database for the period 2001-2020. The purpose of the study is to understand the status of NLP research at the global, national, institutional, and author level. The study highlights the productivity and performance of NLP research on a series of metrics as well as provides a visual view of collaborative network relationship between authors, research institutions, and leading countries using standard software tools. In addition, the study identified the leading players in NLP research such as key countries, institutions, authors, and areas of research. According to the study, the USA leads in global publications output as well as it leads in terms of relative citation index.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"38 4 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association between Mendeley early readership and later citations in library and information science journals","authors":"L. Parabhoi, Damodar Parabhoi, Ramani Ranjan Sahu, M. Verma, R. S. Dewey","doi":"10.47974/cjsim-2022-0074","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0074","url":null,"abstract":"Altmetrics indicators are useful for assessing the impact of research and have been increasingly used alongside traditional citations in recent years. Mendeley provides readership statistics which give an early indicator of the impact of research outputs. This study aimed to investigate how Mendeley early readership indicator was associated with later citations across nine selected library and information science (LIS) journals. This study examined bibliographic data of 9 LIS journals extracted from the Scopus database over a 17 months period from June 2019 to November 2020. Data were extracted using Webometric Analyst. Spearman’s rank correlation coefficient was used to characterize the relationship between these two variables. The number of readers per paper, and of each journal are described using mean, standard deviation, frequency, and geometric mean. Readership growth was increased in all selected journals, but citation growth was unstable in most of the journals. Early readership statistics positively correlated with early citation analysis in all journals except the Journal of Educational Media and Library Science, which had a weaker positive correlation. The correlation between early readership and later citation numbers varied, with some journals being moderately positive and some weakly positive.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping of top papers in the subject category of Soil Science","authors":"Jie Sun, Bao-Zhong Yuan","doi":"10.47974/cjsim-2020-0097","DOIUrl":"https://doi.org/10.47974/cjsim-2020-0097","url":null,"abstract":"Based on the ESI database, this study analyzed 612 top papers in the subject category of soil science from 2009 to 2019, which includes 608 highly cited papers and 17 hot papers, of which 4 are only hot papers and other 13 papers are both hot papers and highly cited papers. Top 5 core journals with higher impact factor ranked as Soil Biology Biochemistry, Geoderma, Plant and Soil, Catena, Soil Tillage Research. Top 5 countries and regions were Peoples R China, USA, Germany, Australia, France. The study also analysed that top 5 organizations were Chinese Acad Sci, Univ Western Australia, Univ Chinese Acad Sci, INRA, Nanjing Agr Univ. The analysis of all keywords showed that the research was separated in clusters. Therefore, authors can choose their ideal journal with a high impact factor to publish papers in the English language related to this research field.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70463997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamics of Scientometrics Indicators in three distinct Physics Journals with long publication history","authors":"Abinash Panda, B. Maharana, S. Sahu","doi":"10.47974/cjsim-2022-0067","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0067","url":null,"abstract":"Core journals in any subject go through evolution processes before being accepted worldwide. The study of the journal’s evolution with its long publication history gives insight into distinct characteristics acquired over time. This study explores the dynamics in scientometrics indicators of three distinct Physics journals with the same scope but published from different regions and impact factors. The result shows each journal has its discrete contributors, but the host or home country contributes more than 50%. In short or medium duration (decadal), the increase in authorship per article differs from journal to journal. Still, the change is approximately the same over a longer duration (1990-2019) (46.38% to 48.5%). A journal with linear authorship growth only correlates significantly with its impact factor (r = 0.877). These journals also show an increase in international coauthored publications, but the increase mostly depends on the host country’s collaborations. More than 80% of associations are between two countries. The findings establish that irrespective of Physics’s global use and implications, the researchers tend to publish in familiar journals from their region regardless of impact factors. The journals with higher impact factors publish more transnational articles.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scientific activities, and extent of collaborative efforts in the top academic institutions of India : A scientometric study using Web of Science data","authors":"Saloni Chaudhary, Bhaskar Mukherjee","doi":"10.47974/cjsim-2022-0043","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0043","url":null,"abstract":"Using more than one lakh publication records from the Web of Science database, we tried to identify the scientific activity (publications, collaborations and citations), sectors of collaboration (University- Industry-Government), & subjects of collaboration in the top 10 NIRF ranked engineering institutes and universities in India. The study indicated that collaboration in different types of academic institutions has steadily increased from 2011 to 2020. Greater growth has been observed in domestic collaboration than foreign collaboration. The international collaboration network tends to be very dense with more advantageous countries. Although, international collaboration resulting in more citations, the fractional impact strength of domestic publications is better than foreign. The impact factor of the journal was observed to be a better predictor than the number of authors per article. University-University sector – mainly different departments of the same institute emerge as the predominant form of domestic collaborative research. While assessing the disciplinary output of the top 10 institutions by establishing a subject framework based on the Frascati Manual and Essential Science Indicator of Clarivate, it was observed that Civil, Mechanical & Electrical Engineering; Chemical, Material & Environmental Engineering; Chemical Sciences, and Theoretical aspects of Physics were the major fields amongst science disciplines with overall 52% of domestic and 48% of foreign collaboration.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A drop of quantum dots in the ocean of quantum computing","authors":"Shradha Deshmukh, Preeti Mulay","doi":"10.47974/cjsim-2022-0050","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0050","url":null,"abstract":"The composition tunable and special size electronic feature of quantum dots makes promising feature of quantum dots and promising number of new technologies and applications. Understanding the research patterns and opportunities in the field of quantum dots, gives birth to advanced technologies. Nowadays it is essential to examine the transition in artificial atoms that is quantum dots to the next generation evolution and biosafety. The paper gives the analysis of scientific publications in the field of quantum dots. The quantitative and qualitative analysis of the research publication of quantum dots in quantum computing revealed the emerging sub-field and future development trends. The paper focuses on the relevant publications from 1986 to early mid of 2022, using Scopus and Web of Science research database. Using the popular search keywords, the analysis not only focuses on trends of the quantum dots in quantum computing but also points out future directions for the researchers.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patentometric review on automated plant phenotyping","authors":"Shrikrishna Kolhar, Jayant Jagtap, A. Tiwari","doi":"10.47974/cjsim-2022-0047","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0047","url":null,"abstract":"Plant phenotyping involves the measurement of observable traits of plants. Plant traits like leaf area, leaf count, leaf surface temperature, chlorophyll content, plant growth rate, emergence time of leaves, and reproductive organs depend on the interaction of its genotype with the environment. Plant phenotyping serves to analyze biotic and abiotic stresses on plants, select crop varieties resilient to the surrounding environment, and improve crop yield. Recent advancements in imaging technologies help expedite the growth of automatic, non-invasive, and efficient plant phenotyping systems. These plant phenotyping systems involve using different imaging techniques like visible imaging, hyperspectral imaging, chlorophyll fluorescence imaging (CFIM), thermal imaging to record, monitor, and analyze plant phenotypes using images. In the last few years, researchers have been working on developing image processing, computer vision, machine learning, and deep learning approaches for the accurate and precise analysis of plant images. Therefore, this paper reviews and presents insights about the research reported through patents in the area of automatic plant phenotyping. This review report uses patent databases like Espacenet, Lens, and Google Patents to search, review and analyze patent documents. The paper presents a patentometric analysis of all 67 patent documents available till date focusing on automatic image-based plant phenotyping. The review provides a summary and analysis of outstanding patents in terms of qualitative and quantitative patent indices. This article provides a comprehensive global patent study to aid researchers and scientists develop more efficient plant phenotyping algorithms, devices, and systems.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classic articles in cervical cancer research : A bibliometric analysis","authors":"O. Tantengco, Y. Ho","doi":"10.47974/cjsim-2022-0029","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0029","url":null,"abstract":"Background: Analyzing classic articles or research papers that received total citations of 1000 or more has helped study the evolution of research trends and identify research gaps and future directions in a particular field. This study used a bibliometric approach to analyzing classic articles in cervical cancer research. Method: Classic articles in cervical cancer research with 1,000 or more citations from the Web of Science Core Collection from publication to the end of 2020 were analyzed using bibliometric analysis. These methods determine the document types, most productive countries, institutions, and journals for classic articles in cervical cancer research. Moreover, it also determined their research impact through the years by analyzing their citation histories. Result: We documented 46 classic cervical cancer research papers published in the Web of Science from 1983 until 2019. The CA-A Cancer Journal for Clinicians and the New England Journal of Medicine were the most productive journals that published seven classic cervical cancer articles. The USA was the most productive country, with 28 classic cervical cancer articles. The International Agency for Research on Cancer in France and the American Cancer Society in the USA were the most effective and impactful institutions in cervical cancer research. Citation histories revealed that the most important and cited papers in recent years were cancer statistics that report incidence and mortality from cervical cancer worldwide. The most impactful studies include articles on HPV as a necessary cause of cervical cancer, the discovery and development of HPV vaccines to prevent cervical cancer, and the development of chemotherapy, radiotherapy, and surgical treatment for cervical cancer. Conclusion: This study showed cervical cancer research’s most productive countries, institutions, and journals. It also demonstrated the citation history of these classic articles, which showed influential studies still relevant to cervical cancer research until recently.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}