Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.049
Anup Kumar Das
{"title":"South Asian Science Diplomacy in a Nutshell","authors":"Anup Kumar Das","doi":"10.5530/jscires.12.2.049","DOIUrl":"https://doi.org/10.5530/jscires.12.2.049","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"23 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82532218","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.042
A. Müngen
This study investigates the variations in lexical richness within English language theses across diverse disciplines, focusing on areas where researchers exhibit higher degrees of lexical richness and the evolution of vocabulary usage over time. By analyzing these variations, the research aims to provide insights into the effective use of lexical richness in academic writing and contribute to the development of more engaging and comprehensible scholarly publications. A total of 320 theses were randomly selected from the Turkey National Thesis Center and classified according to their scientific discipline. Using natural language processing techniques, unique word count, word diversity, and other metrics were analyzed. Results reveal that social sciences tend to exhibit higher lexical richness compared to natural sciences, and no significant difference was observed in word richness between social and natural sciences disciplines. These findings contribute to the understanding of lexical richness in academic writing and highlight the importance of achieving a balance between lexical richness and readability.
{"title":"Exploring Lexical Richness in English-Language theses Across Disciplines: A Comparative Analysis","authors":"A. Müngen","doi":"10.5530/jscires.12.2.042","DOIUrl":"https://doi.org/10.5530/jscires.12.2.042","url":null,"abstract":"This study investigates the variations in lexical richness within English language theses across diverse disciplines, focusing on areas where researchers exhibit higher degrees of lexical richness and the evolution of vocabulary usage over time. By analyzing these variations, the research aims to provide insights into the effective use of lexical richness in academic writing and contribute to the development of more engaging and comprehensible scholarly publications. A total of 320 theses were randomly selected from the Turkey National Thesis Center and classified according to their scientific discipline. Using natural language processing techniques, unique word count, word diversity, and other metrics were analyzed. Results reveal that social sciences tend to exhibit higher lexical richness compared to natural sciences, and no significant difference was observed in word richness between social and natural sciences disciplines. These findings contribute to the understanding of lexical richness in academic writing and highlight the importance of achieving a balance between lexical richness and readability.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"162 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74080396","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.045
Mohammad Haris, P.M. Naushad Ali, Priya Vaidya
The present study intends to explore the overall research performance/engagement of the faculty members on the ResearchGate from the Physics discipline working at Indian Central Universities. The analyzed data revealed that 473 faculty members were found, but only 361 (i.e., 76.32%) have their profile on ResearchGate. Further analyses include the distribution of RG metrices which indicated that 98.89% and 98.06% of the faculty members had added at least one research item and at least one full-text research item over the RG, respectively. The findings stated that Kriti Ranjan from the University of Delhi secured highest ranking across all metrices, except followers and followings. The mean value for the Reads and Citations were found to be 27525.59 (std. dev. = 163029.86) and 1555.2 (std. dev. = 5838.76), respectively. In addition, RI Score exhibits a strong positive correlation with other RG-based metrices excluding the ‘following’. This study can be considered the only ResearchGate analyses that has included the working researchers of the Physics discipline by analyzing their research engagement and active presence over it.
{"title":"Assessment of ResearchGate to Unfurl the Academic Pursuits of Physics Scholars","authors":"Mohammad Haris, P.M. Naushad Ali, Priya Vaidya","doi":"10.5530/jscires.12.2.045","DOIUrl":"https://doi.org/10.5530/jscires.12.2.045","url":null,"abstract":"The present study intends to explore the overall research performance/engagement of the faculty members on the ResearchGate from the Physics discipline working at Indian Central Universities. The analyzed data revealed that 473 faculty members were found, but only 361 (i.e., 76.32%) have their profile on ResearchGate. Further analyses include the distribution of RG metrices which indicated that 98.89% and 98.06% of the faculty members had added at least one research item and at least one full-text research item over the RG, respectively. The findings stated that Kriti Ranjan from the University of Delhi secured highest ranking across all metrices, except followers and followings. The mean value for the Reads and Citations were found to be 27525.59 (std. dev. = 163029.86) and 1555.2 (std. dev. = 5838.76), respectively. In addition, RI Score exhibits a strong positive correlation with other RG-based metrices excluding the ‘following’. This study can be considered the only ResearchGate analyses that has included the working researchers of the Physics discipline by analyzing their research engagement and active presence over it.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"302 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74889950","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.020
Atul Kumar, Jaiprakash M. Paliwal, Vinaydeep Brar, Mahesh Singh, Prashant R Tambe Patil, S. Raibagkar
Over the last few years, CiteScore has emerged as a popular metric to measure the performance of Journals. In this paper, we analyze CiteScores of the top 400 Scopus-indexed journals of 2021 for years from 2011 to 2021. Some interesting observations emerged from the analysis. The average CiteScore of the top 400 journals doubled from 16.48 in 2011 to 31.83 in 2021. At the same time, the standard deviation has almost trebled from 13.53 in 2011 to 38.18 in 2021. The CiteScores also show sizable increases for skewness and kurtosis, implying major variations in the CiteScores of the journals for a year. Importantly, the previous year’s CiteScores strongly predict the next year’s scores. This has been observed consistently for the last ten years. The average Pearson correlation coefficient between the preceding and succeeding years’ CiteScores for the ten years is 0.98. We also show that it is easily possible for even people with just basic knowledge of computers to forecast the CiteScore. Researchers can predict CiteScores based on the past year’s CiteScores and decide better about publishing their current research in a journal with an idea about its likely CiteScore. Such a forecast can be useful to publishers, editorial staff, indexing services, university authorities, and funding agencies.
{"title":"Previous Year’s Cite Score Strongly Predicts the Next Year’s Score: Ten Years of Evidence for the Top 400 Scopus-indexed Journals of 2021","authors":"Atul Kumar, Jaiprakash M. Paliwal, Vinaydeep Brar, Mahesh Singh, Prashant R Tambe Patil, S. Raibagkar","doi":"10.5530/jscires.12.2.020","DOIUrl":"https://doi.org/10.5530/jscires.12.2.020","url":null,"abstract":"Over the last few years, CiteScore has emerged as a popular metric to measure the performance of Journals. In this paper, we analyze CiteScores of the top 400 Scopus-indexed journals of 2021 for years from 2011 to 2021. Some interesting observations emerged from the analysis. The average CiteScore of the top 400 journals doubled from 16.48 in 2011 to 31.83 in 2021. At the same time, the standard deviation has almost trebled from 13.53 in 2011 to 38.18 in 2021. The CiteScores also show sizable increases for skewness and kurtosis, implying major variations in the CiteScores of the journals for a year. Importantly, the previous year’s CiteScores strongly predict the next year’s scores. This has been observed consistently for the last ten years. The average Pearson correlation coefficient between the preceding and succeeding years’ CiteScores for the ten years is 0.98. We also show that it is easily possible for even people with just basic knowledge of computers to forecast the CiteScore. Researchers can predict CiteScores based on the past year’s CiteScores and decide better about publishing their current research in a journal with an idea about its likely CiteScore. Such a forecast can be useful to publishers, editorial staff, indexing services, university authorities, and funding agencies.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"43 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80642455","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.029
Isaac Appiah-Otoo
This study utilizes a scientometric/bibliometric analysis to map the status quo of research on finance-growth from 2005 to 2022. By using a sample of 404 articles from the Web of Science Core Collection database and the VOSviewer computer software, the study documented the following: First, research on finance-growth has reached the growth stage with 2021 recording the highest number of publications. Second, business and economics journals have published the largest number of articles. Besides, the USA and China have produced the largest number of articles while Eastern Mediterranean University, Monash University, and Universiti Sains Malaysia are the leading institutions in finance-growth research. Furthermore, Levine Ross, Beck Thorsten, and King Robert can be credited with the modern finance-growth thesis. Finally, economic growth and financial development are the leading keywords in the field.
本研究采用科学计量与文献计量相结合的方法，对2005 - 2022年金融增长研究现状进行了分析。本研究以Web of Science Core Collection数据库中的404篇文章为样本，利用VOSviewer计算机软件进行研究，结果表明:第一，财务增长研究进入成长期，2021年的论文发表量最高。其次，商业和经济类期刊发表的文章最多。此外，美国和中国发表的论文数量最多，而东地中海大学、莫纳什大学和马来西亚理科大学是金融增长研究的领先机构。此外，莱文·罗斯、贝克·托尔斯滕和金·罗伯特也被认为是现代金融增长理论的创始人。最后，经济增长和金融发展是该领域的主导关键词。
{"title":"A Bibliometric Assessment of the Finance-growth Literature: Current Status, Development and Future Direction","authors":"Isaac Appiah-Otoo","doi":"10.5530/jscires.12.2.029","DOIUrl":"https://doi.org/10.5530/jscires.12.2.029","url":null,"abstract":"This study utilizes a scientometric/bibliometric analysis to map the status quo of research on finance-growth from 2005 to 2022. By using a sample of 404 articles from the Web of Science Core Collection database and the VOSviewer computer software, the study documented the following: First, research on finance-growth has reached the growth stage with 2021 recording the highest number of publications. Second, business and economics journals have published the largest number of articles. Besides, the USA and China have produced the largest number of articles while Eastern Mediterranean University, Monash University, and Universiti Sains Malaysia are the leading institutions in finance-growth research. Furthermore, Levine Ross, Beck Thorsten, and King Robert can be credited with the modern finance-growth thesis. Finally, economic growth and financial development are the leading keywords in the field.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"26 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77850890","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.025
Ma. Elena Luna-Morales, M. A. Pérez-Angón, Evelia Luna-Morales
We carried out a bibliometric analysis of the research production in the field of evolutionary computation in Latin America (LA) for the period 1980-2020. The bibliometric method is applied with a quantitative review of the published literature. The search for publications was carried out in the Web of Science database through the terms that are most commonly used to identify this field of study. The data analysis the data analysis used Microsoft Office tools (excel and Access) to organize our data were used to organize our data: authors, institutions, journals, countries and thematic categories. It was completed with VOS Viewer 1.8.16 to generate a co-authorship network map of authors, and the development of base maps for collaboration by countries. We have identified the first Latin American publications in the journals Archivos de Biologia y Medicina Experimentales and Desarrollo Economico-Revista de Ciencias Sociales; this research field reached a consolidation in the 2000s with the opening of the first graduate programs in this geographical region; there is an extraordinary number of LA scholars active in this research field and an increasing number of academic institutions mainly from Brazil, Mexico, Argentina, Chile and Colombia; while the Asian and European production in this research field is about 30%, the respective LA contribution is just 4.9%. The present study attempts to document the progress of evolutionary computation in Latin America, an issue that has gained relevance for society, especially in recent years. No studies have been generated that cover the Latin American region, and therefore it is hoped that these findings will be useful for the development of scientific and public policies and also for other future work.
我们对拉丁美洲(LA) 1980-2020年进化计算领域的研究成果进行了文献计量分析。应用文献计量学方法对已发表的文献进行定量回顾。出版物的搜索是在Web of Science数据库中通过最常用的术语进行的，这些术语用于识别该研究领域。数据分析数据分析使用Microsoft Office工具(excel和Access)来组织我们的数据使用作者，机构，期刊，国家和专题类别来组织我们的数据。它是用VOS Viewer 1.8.16完成的，以生成作者的合作网络地图，并开发供各国合作的基础地图。我们已经在《生物学与医学实验档案》和《社会科学经济评论》杂志上确定了第一批拉丁美洲出版物;这一研究领域在2000年代随着该地理区域第一批研究生课程的开设而得到巩固;活跃在这一研究领域的洛杉矶学者数量惊人，越来越多的学术机构主要来自巴西、墨西哥、阿根廷、智利和哥伦比亚;亚洲和欧洲在这一研究领域的贡献约为30%，而各自的LA贡献仅为4.9%。本研究试图记录拉丁美洲进化计算的进展，这是一个与社会相关的问题，特别是近年来。目前还没有关于拉丁美洲区域的研究报告，因此希望这些研究结果将有助于制定科学和公共政策，也有助于今后的其他工作。
{"title":"Strengthen of a Scientific Field in Latin America: Evolutionary Computation","authors":"Ma. Elena Luna-Morales, M. A. Pérez-Angón, Evelia Luna-Morales","doi":"10.5530/jscires.12.2.025","DOIUrl":"https://doi.org/10.5530/jscires.12.2.025","url":null,"abstract":"We carried out a bibliometric analysis of the research production in the field of evolutionary computation in Latin America (LA) for the period 1980-2020. The bibliometric method is applied with a quantitative review of the published literature. The search for publications was carried out in the Web of Science database through the terms that are most commonly used to identify this field of study. The data analysis the data analysis used Microsoft Office tools (excel and Access) to organize our data were used to organize our data: authors, institutions, journals, countries and thematic categories. It was completed with VOS Viewer 1.8.16 to generate a co-authorship network map of authors, and the development of base maps for collaboration by countries. We have identified the first Latin American publications in the journals Archivos de Biologia y Medicina Experimentales and Desarrollo Economico-Revista de Ciencias Sociales; this research field reached a consolidation in the 2000s with the opening of the first graduate programs in this geographical region; there is an extraordinary number of LA scholars active in this research field and an increasing number of academic institutions mainly from Brazil, Mexico, Argentina, Chile and Colombia; while the Asian and European production in this research field is about 30%, the respective LA contribution is just 4.9%. The present study attempts to document the progress of evolutionary computation in Latin America, an issue that has gained relevance for society, especially in recent years. No studies have been generated that cover the Latin American region, and therefore it is hoped that these findings will be useful for the development of scientific and public policies and also for other future work.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"8 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84211964","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.036
Anjali Yadav, Arpana Pandey, Chanchal Chanchal
Menstrual health has reaped much attention with a swift increase in the related literature. This study intended to map the knowledge landscape of menstrual health research in India using a scientometric and information visualization approach. The scientometric analysis of Scopus data on parameters like publication output, publication share, growth rate, prolific authors, authorship pattern, scientific fields, citation analysis, international collaboration, etc., has been conducted. 52257 publications were produced globally during the study period, with 2668 papers from India. The majority of these research output is collaborative and multi-authored. America is the most productive country and India's top collaborative associate in menstrual studies. All India Institute of Medical Sciences and Clinical and Diagnostic Research journal is the most efficient institute and journal. Moreover, menstrual health, menstrual cycle and menstrual hygiene, menstrual syndrome, and studies on the function of hormones in menstruation were diagnosed as the mainstream topics in the fields of menstrual health. The study's findings will offer proof of the current status and trends in menstrual health. They will assist researchers and policymakers in understanding the panorama of menstrual health and expecting the dynamic research guidelines.
{"title":"Identification and Visualization of the Knowledge Landscape of Menstrual Health Research in India: 1996-2020","authors":"Anjali Yadav, Arpana Pandey, Chanchal Chanchal","doi":"10.5530/jscires.12.2.036","DOIUrl":"https://doi.org/10.5530/jscires.12.2.036","url":null,"abstract":"Menstrual health has reaped much attention with a swift increase in the related literature. This study intended to map the knowledge landscape of menstrual health research in India using a scientometric and information visualization approach. The scientometric analysis of Scopus data on parameters like publication output, publication share, growth rate, prolific authors, authorship pattern, scientific fields, citation analysis, international collaboration, etc., has been conducted. 52257 publications were produced globally during the study period, with 2668 papers from India. The majority of these research output is collaborative and multi-authored. America is the most productive country and India's top collaborative associate in menstrual studies. All India Institute of Medical Sciences and Clinical and Diagnostic Research journal is the most efficient institute and journal. Moreover, menstrual health, menstrual cycle and menstrual hygiene, menstrual syndrome, and studies on the function of hormones in menstruation were diagnosed as the mainstream topics in the fields of menstrual health. The study's findings will offer proof of the current status and trends in menstrual health. They will assist researchers and policymakers in understanding the panorama of menstrual health and expecting the dynamic research guidelines.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"65 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89615495","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.031
Paula Marques Borges Vinhas Porto, Sabrina de Oliveira Anício, Rodrigo Nogueira Vasconcelos, T. Malheiros, Washington de Jesus Sant’Anna da Franca Rocha
Biogas, a by-product of effluent treatment, is increasingly no longer seen as a passive, taking on the role of an asset. This work carried out a bibliometric study of the world production of biogas from domestic wastewater, focusing on the evolution of knowledge over the decades. For this purpose, a search for scientific articles was carried out in the Scopus database and, from the documents obtained, a review of literature was developed to access information and reveal quantification patterns. The analysis of the graphs and networks generated proved efficient in the exploratory study of the scientific and technological evolution of biogas from domestic sewage, making it possible to observe a highlight for the recovery of dissolved methane, as well as for the gains in reducing emissions of GHG from biogas reuse, in addition to the focus on nutrient and energy recovery, which underscores the importance of anaerobic processes for obtaining energy and nutrient conservation, as well as their potential contribution to achieving the goals related to the Sustainable Development Goals.
{"title":"Energy Recovery from Biogas in Domestic Waste Water Treatment Plant in the Last 5 Decades: A Bibliometric Analysis","authors":"Paula Marques Borges Vinhas Porto, Sabrina de Oliveira Anício, Rodrigo Nogueira Vasconcelos, T. Malheiros, Washington de Jesus Sant’Anna da Franca Rocha","doi":"10.5530/jscires.12.2.031","DOIUrl":"https://doi.org/10.5530/jscires.12.2.031","url":null,"abstract":"Biogas, a by-product of effluent treatment, is increasingly no longer seen as a passive, taking on the role of an asset. This work carried out a bibliometric study of the world production of biogas from domestic wastewater, focusing on the evolution of knowledge over the decades. For this purpose, a search for scientific articles was carried out in the Scopus database and, from the documents obtained, a review of literature was developed to access information and reveal quantification patterns. The analysis of the graphs and networks generated proved efficient in the exploratory study of the scientific and technological evolution of biogas from domestic sewage, making it possible to observe a highlight for the recovery of dissolved methane, as well as for the gains in reducing emissions of GHG from biogas reuse, in addition to the focus on nutrient and energy recovery, which underscores the importance of anaerobic processes for obtaining energy and nutrient conservation, as well as their potential contribution to achieving the goals related to the Sustainable Development Goals.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"93 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78651924","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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.024
Mayur Makawana, Rupa G. Mehta
As part of the research process, relevant documents are identified to keep up with the latest advancements in the domain. Document recommendation systems are used by researchers as a means of accomplishing this goal. Textual content, collaborative filtering, and citation information-based approaches are among the proposed approaches for the recommendation systems. Content-based techniques take advantage of the entire text of papers and produce more promising results, but comparing input document text data to every document in the dataset is not practical for the content-based recommender system. This study looks into the possibility of using bibliographic data to reduce the number of comparisons. The proposed system is based on the assumption that two scientific papers are semantically connected if they are co-cited more frequently than by chance. The likelihood of co-citation, also known as semantic relatedness, can be used to quantify this connection. This work presents a new way to distribute the weight among connected scholarly documents based on a semantic relatedness score. Our proposed solution eliminates a substantial amount of needless text comparisons for the system by gathering scholarly document pairs with high likelihood values and using them as a search area for the content-based recommender system. By spreading the co-citation relationship out to certain distances, the proposed approach can find relevant documents that are not found by traditional co-citation searches. The results reveal that the system is capable of reducing computations by a significant margin and of detecting false positive situations in content comparison using Doc2vec.
{"title":"Discovering Search Space Using M-distance Clustering of Semantic Relatedness Based Weighted Network for the Content-based Recommender System","authors":"Mayur Makawana, Rupa G. Mehta","doi":"10.5530/jscires.12.2.024","DOIUrl":"https://doi.org/10.5530/jscires.12.2.024","url":null,"abstract":"As part of the research process, relevant documents are identified to keep up with the latest advancements in the domain. Document recommendation systems are used by researchers as a means of accomplishing this goal. Textual content, collaborative filtering, and citation information-based approaches are among the proposed approaches for the recommendation systems. Content-based techniques take advantage of the entire text of papers and produce more promising results, but comparing input document text data to every document in the dataset is not practical for the content-based recommender system. This study looks into the possibility of using bibliographic data to reduce the number of comparisons. The proposed system is based on the assumption that two scientific papers are semantically connected if they are co-cited more frequently than by chance. The likelihood of co-citation, also known as semantic relatedness, can be used to quantify this connection. This work presents a new way to distribute the weight among connected scholarly documents based on a semantic relatedness score. Our proposed solution eliminates a substantial amount of needless text comparisons for the system by gathering scholarly document pairs with high likelihood values and using them as a search area for the content-based recommender system. By spreading the co-citation relationship out to certain distances, the proposed approach can find relevant documents that are not found by traditional co-citation searches. The results reveal that the system is capable of reducing computations by a significant margin and of detecting false positive situations in content comparison using Doc2vec.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"7 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85691159","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}
The article aimed to develop a systematic review of the scientific literature about indicators for the evaluation of science, technology and innovation activities. For this, the Web of Science, Scopus and Google Scholar databases were used. Through the application of the SysteRe-HSS methodology, 96 publications were selected that formed the basis for a descriptive model of the science, technology and innovation indicators. The results of the research showed that there is a predominance of indicators related to the evaluation of innovation activities, human resources allocated to the activity of science, technology and innovation, financial resources and investments in research plus development, and indicators related to bibliometrics and scientometrics. However, challenges are faced related to measuring indicators of social innovation, linking insights from existing innovation measurement approaches with the essential features of social innovation, measuring the impact of social appropriation practices of science and technology, and the next generation metrics, responsible metrics and evaluation for open science, as well as alternative indicators for the evaluation of the social impact of research in web 2.0.
本文旨在对科学、技术和创新活动评价指标的科学文献进行系统的综述。为此，我们使用了Web of Science、Scopus和Google Scholar数据库。通过应用system - hss方法，选择了96份出版物，这些出版物构成了科学、技术和创新指标描述性模型的基础。研究结果表明，创新活动评价指标、科技创新活动人力资源配置指标、研发投入指标、文献计量学指标和科学计量学指标占主导地位。然而，在衡量社会创新指标、将现有创新测量方法的见解与社会创新的本质特征联系起来、衡量科学技术的社会占有实践的影响、下一代指标、开放科学的负责任指标和评估以及评估web 2.0下研究的社会影响的替代指标方面面临着挑战。
{"title":"Indicators for the Evaluation of Science, Technology and Innovation Activities: A Systematized Review","authors":"Roelvis Ortiz-Núñez, Stephany Novo-Castro, Ricardo Casate-Fernández","doi":"10.5530/jscires.12.2.041","DOIUrl":"https://doi.org/10.5530/jscires.12.2.041","url":null,"abstract":"The article aimed to develop a systematic review of the scientific literature about indicators for the evaluation of science, technology and innovation activities. For this, the Web of Science, Scopus and Google Scholar databases were used. Through the application of the SysteRe-HSS methodology, 96 publications were selected that formed the basis for a descriptive model of the science, technology and innovation indicators. The results of the research showed that there is a predominance of indicators related to the evaluation of innovation activities, human resources allocated to the activity of science, technology and innovation, financial resources and investments in research plus development, and indicators related to bibliometrics and scientometrics. However, challenges are faced related to measuring indicators of social innovation, linking insights from existing innovation measurement approaches with the essential features of social innovation, measuring the impact of social appropriation practices of science and technology, and the next generation metrics, responsible metrics and evaluation for open science, as well as alternative indicators for the evaluation of the social impact of research in web 2.0.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"15 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78278245","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}
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