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LLM - Digital Humanities 16

ERROR: type should be string, got "https://doi.org/10.18280/ijdne.180606 \nABSTRACT https://doi.org/10.18280/ijdne.180606 \nABSTRACT \nReceived: 23 October 2023 \nRevised: 9 November 2023 \nAccepted: 15 December 2023 \nAvailable online: 26 December 2023 \nThe evolution o\naffecting childre\nevaluated throu\nthousand one hu\nof Science and S The evolution of poliomyelitis (polio) research, an acute viral infection predominantly \naffecting children and ranging from mild illness to disabling paralysis, was systematically \nevaluated through a bibliometric analysis of publications from 1857 to 2019. Six \nthousand one hundred thirty-nine polio-related publications were extracted from the Web \nof Science and Scopus databases, employing 'Polio' as the keyword. Publications were \npredominantly in article format (71.16%), with English-language documents constituting \n30% of the dataset. The analysis, executed using EndNote, Microsoft Excel, R \n(Biblioshiny), and VOSviewer, identified 2014 as the peak year of polio literature output, \nfeaturing 340 publications. A shift from single to collaborative authorship was observed, \nwith multiple authorship patterns emerging more prominently. This trend highlights a \ntransition towards interdisciplinary collaboration in the field. Despite the dominance of \narticles, a diverse array of sixteen document types was catalogued. The journal 'Vaccine' \nwas the pivotal publication venue, representing a nexus for polio-related discourse. The \ninstitutional analysis placed the World Health Organization at the epicenter of polio \nresearch, with universities and private research entities following suit. The geographical \nspread of contributions was vast, covering 114 regions. Nonetheless, a significant \nproportion of the literature (33.5%) remained uncited, suggesting an untapped potential \nfor research impact. Citation analysis yielded an average citation rate of 9.52%, and co-\ncitation analysis unveiled a network of 4,758 references despite incomplete citation data \nin several records. Visualization maps elucidated recurrent thematic terms such as 'polio', \n'children', 'eradication', 'vaccine', and 'virus', indicating the focal points of scholarly \ncommunication. This study not only delineates the historiography of polio research but \nalso underscores the necessity for enhanced dissemination and integration of findings to \nfortify the global health response to poliomyelitis. Keywords: \nvirus, poliomyelitis, citation analysis, research \ntrends, public health, scientometrics, Web of \nScience, Scopus International Journal of Design & Nature and Ecodynamics \nVol. 18, No. 6, December, 2023, pp. 1333-1346 \nJournal homepage: http://iieta.org/journals/ijdne International Journal of Design & Nature and Ecodynamics \nVol. 18, No. 6, December, 2023, pp. 1333-1346 \nJournal homepage: http://iieta.org/journals/ijdne lobal Trends in Poliomyelitis Research: A Bibliometric Analysis from 1857–2019 Shiza Shamin1\n, Malik Muhammad Saad Missen1\n, Ali Mustafa Qamar2*\n, Amnah Firdous3\n, Qurat Ul Ain1\n, \nV. B. Surya Prasath4,5 1 Department of Computer Science and IT, The Islamia University, Bahawalpur 63100, Pakistan \n2 Department of Computer Science, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia \n3 Department of Computer Science and IT, Government Sadiq College Women University, Bahawalpur 63100, Pakistan \n4 Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center 3333 Burnet Ave, Cincinnati 45229, USA \n5 Departments of Biomedical Informatics, Electrical Engineering and Computer Science University of Cincinnati, Cincinnati \n45221, USA 4 Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center 3333 Burnet Ave, Cincinnati 45229, USA \n5 Departments of Biomedical Informatics, Electrical Engineering and Computer Science University of Cincinnati, Cincinnati \n45221, USA Corresponding Author Email: al.khan@qu.edu.sa Corresponding Author Email: al.khan@qu.edu.sa Copyright: ©2023 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license \n(http://creativecommons.org/licenses/by/4.0/). 2. LITERATURE REVIEW A lot of bibliometric analysis research was done in the field \nof medical sciences. Here, we review some related literature \nrelated to medical sciences, such as the analysis of critical \nissues in healthcare integrity. Pandey et al. [1] analyze \nessential healthcare integrity matters. They report that \nmanaging data integrity is a difficult task for the researcher. Therefore, this study makes a scientometrics analysis of the \nresearch publications in healthcare data integrity. This paper \nhighlights the data integrity issues in healthcare and provides \na literature review of the previous findings. Moreover, they \ndiscuss the methodology and issues and give a road map to \nfuture researchers by giving them various ideas. The \nconcluding part of the paper presents an objective and \nsensitivity analysis for finding the difficulties in the studies \nwhile informing about the feasible solutions. Hossain [4] discussed in his work that the coronavirus \n(COVID-19) disease is the primary health concern due to its \ninfective and global distribution. He performed the \nbibliometric analysis to evaluate the current scientific \nliterature to find the development of knowledge on \ncoronavirus. A total of 422 records were extracted, with 1,652 \nauthors. One thousand five hundred eighty-one documents had \nmultiple-authored documents. Moreover, 2.47 citations were \nreceived on average for each document. The author, E. Mahase, had the highest number of publications (n=13). It also \nincludes information about the top 10 journals which publish \narticles on COVID-19. British Medical Journal was the top \njournal with 47 articles. We believe the data could be more \nextensive according to the state-of-the-art bibliometric \nanalysis of COVID-19. Even the number of publications \nconsidered in our research is more than ten times. g\nEsmaeilpour-Bandboni et al. [2] conducted a bibliometric \nanalysis aimed at performing analysis of Radiology, Nuclear \nMedicine, and Medical Imaging articles written by Iranian \nresearchers, published in journals and extracted from WoS and \nScopus databases from 2001 to 2016. Three thousand three \nhundred thirty-five documents were retrieved. HistCite, \nMicrosoft Excel, and VOSviewer were used to analyze the \ndata. The study analyzes that Iran’s contribution was meagre \nin both databases, i.e., WoS (0.32%) and Scopus (0.52%). The \nTehran University of Medical Sciences was the database's \nmost contributing institution. According to these findings, the \nstudy concludes that Iran may contribute with the USA, Japan, \nand Germany to increase the publication count. 1. INTRODUCTION potentially leading to paralysis. Globally, two types of vaccines are instrumental in the fight \nagainst polio. Both are designed to confer immunity and \ninterrupt person-to-person transmission of the virus, thereby \nprotecting individuals and the wider community. The \npioneering vaccine, featuring an attenuated strain of the virus, \nwas developed by microbiologist Hilary Koprowski and first \nadministered to a child in 1950. Subsequently, Jonas Salk \nintroduced an inactivated poliovirus vaccine at the University \nof Pittsburgh in 1952, followed by Albert Sabin's development \nof a live oral vaccine. After three doses, over 95% of recipients \nachieve protection from all three poliovirus types. Notably, \npictorial evidence of polio dates back to prehistoric times. Highly contagious, poliomyelitis (polio) is transmitted \npredominantly via the fecal-oral route, primarily in areas \nafflicted by epidemics, where polioviruses may infect entire \nhuman populations. The disease's latency—from initial \nexposure to symptom onset—usually spans six to twenty days, \nwith a broader range of three to thirty-five days possible. Following infection, viral particles are shed in feces for several \nweeks. Transmission occurs primarily through ingesting \ncontaminated food or water, with secondary transmission via \nthe oral-oral route. The infectious period extends from seven \nto ten days post-symptom onset, but the virus can be excreted \nand potentially transmitted as long as it remains in the feces. Factors such as immune deficiency and malnutrition increase \nsusceptibility to infection and can also exacerbate the severity, Paralytic polio outbreaks, unknown before the 20th century, \nbegan to surface in Europe and the United States around 1900. The first documented outbreak occurred in Louisiana in 1841, 1333 publications on other viral diseases. We discuss the literature \nreview on some diseases and viruses such as COVID-19, \nCoronavirus, Celiac disease, Poliovirus, Echinococcosis \ndisease, \nAlzheimer’s \ndisease, \nLeishmaniasis \ndisease, \nRotavirus, cancer disease and Zika virus. Colavizza et al. [3] \nanalyzed the COVID-19 Open Research Dataset (CORD-19) \nof publications on COVID-19 and coronavirus research. They \ncompare the CORD-19 account with the Web of Science \ndatabase. On one hand, the indication is that CORD-19 \nextends beyond COVID-19 and coronavirus studies. On the \nother hand, it might not encompass a significant portion of the \nliterature solely dedicated to COVID-19 and coronaviruses, \nsuggesting a potential omission in the dataset. They \nthoroughly analyzed CORD-19 in different ways. They \ngenerated a map of interconnected terms sourced from \nCOVID-19 publications. A topic modeling analysis indicated \nthat CORD-19 publications connect to medical research \nencompassing various viruses, including COVID-19 and \ncoronaviruses. 1. INTRODUCTION Predominant themes within CORD-19 include \nstudies on public health, epidemics, molecular biology, and a \nspectrum of viruses like coronaviruses and influenza. Using \nAltmetric data, 46,996 publications were explored on CORD-\n19. They found that 4,096 publications belong to the year \n2020. They selected social media engagements concerning \nCORD-19 publications, focusing on platforms like Altmetric, \nincluding blogs, Twitter, news media, policy documents, and \ncitations in Wikipedia. Notably, Twitter dominated the \ninteractions, comprising over 95% of all social media \ninteractions. News mentions accounted for 3.6% of the \nengagement, followed by blog citations at 0.6%, highlighting \ntheir relative importance in this context. Our research also \nfocuses on a virus. However, the number of publications is \nmuch lesser. with a fifty-year hiatus until a subsequent report of 26 cases in \nBoston in 1893. The widespread adoption of polio vaccines in \nthe 1950s precipitated a marked decrease in incidence across \nmany industrialized nations. In 1988, the World Health \nOrganization (WHO), UNICEF, and The Rotary Foundation \nlaunched a concerted global effort to eradicate polio, which \nachieved a 99% reduction in cases—from an estimated \n350,000 in 1988 to 483 by 2001. Currently, the incidence \nfluctuates between 1,000 to 2,000 cases annually. As of the \nWHO’s 2015 Annual Report, polio remains endemic in \nPakistan and Afghanistan, with sporadic re-emergence in other \nnations, including developed ones. The present study employs a bibliometric approach to \nanalyze a corpus of 6,139 polio-related publications from 1857 \nto 2019, extracted from the Scopus and Web of Science \ndatabases using 'Polio' as the search term. Employing \nanalytical tools such as EndNote, Microsoft Excel, R \n(Biblioshiny), and VOSviewer, the research delineates the \ntrajectory of polio literature, examining document types, \nlanguage distribution, author collaboration patterns, journal \nactivity, and contributions by country and institution, along \nwith citation and co-citation analyses to identify prevailing \nterms in the discourse. This paper is structured as follows: Section 2 presents a \ndetailed literature review, while the methodology is delineated \nin Section 3. Section 4 discusses the experiments and findings, \nand the paper concludes with Section 5, which also provides \nfuture research directions. 2. LITERATURE REVIEW Indian Institute of Chemical \nBiology, Kolkata, has 566 articles published on Leishmaniasis \nand remains at the top. The most active journal in this research \nis PLOS Neglected Tropical Diseases, with 86 publications \nand 2.54% of the share in total papers published. Regarding \ninternational collaboration, India has the most collaborated \nresearch with the USA (339 articles; 10% share). There were \nsix articles which received more than 500 citations. Koster et al. [10] reported that Rotavirus is the leading cause \nof diarrheal disease. Every child in the world is affected by this \ndisease at least once by the age of five. A scientific analysis \nwas made to identify the quantity and quality of research \narticles on Rotavirus. From 1900 to 2013, 5,906 publications \nwere published in 138 countries. The USA authored 2,037 \narticles, accounting for 34.5% of all publications. They also \nmade a gender analysis of authors, finding that most of the \nauthors are women and from Brazil. They also made the \ncooperation and subject analysis. Singh [11] studied the Zika virus, which is transmitted \nthrough the bite of mosquitoes and was initially found in \nmonkeys. Later 1952, it was found in humans in Uganda, \nAmerica, and Africa. It mainly affects pregnant women, \nleading to severe congenital disabilities like microcephaly. After applying a filter to data, 567 documents remained. Lotka’s law was used to analyze the authors’ productivity, and \nBroadford’s law was used to find the distribution pattern of \narticles. The authorship distribution did not align with Lotka’s \nlaw, indicated by a value of n = 2, suggesting an irregular \npattern. However, the distribution of articles across journals \nclosely adhered to Bradford’s law of scattering. This confirms \nthe presence of a select few core journals that significantly \ncontribute to Zika virus research. Ma et al. [7] stated that both humans and animals are \naffected by Echinococcosis disease caused by the larval stage \nof Echinococcus. Scientists tried to minimize this viral \ndisease, but many cases have been reported in the last twenty \nyears. Echinococcus, which is a pandemic, is found in sheep, \ncattle, and dogs. The humans were affected directly or \nindirectly by eating foodstuff or drinking water contaminated \nwith Echinococcosis. This virus causes cysts in organs such as \nthe liver and lungs. The relevant data were retrieved from the \nWeb of Science database, and hot topics and trends about this \ndisease were evaluated. The data were visualized using \nciteSpace software. 2. LITERATURE REVIEW A total of 7,775 articles were downloaded. The period between 2008 and 2017 was found to be a fast \ndevelopment period. France was considered the most \nrepresented country in this research area (n=582/7,688). The \nUniversity of Zurich was at the top. More than 22,445 authors \ncontributed to this research, with P. S. Craig appearing in 171 \npublications. They also analyzed the citations and co-citations. The top cited author was J. Eckert (1,508 citations). Basu et al. [12] discussed the cancer disease and conducted \na scientometric analysis on herbal medicine for cancer \ntreatment. Cancer is increasing health problems worldwide, \nespecially with an increase in city life, population, and changes \nin lifestyle and environment. According to WHO, it is the \nsecond major cause of death worldwide. The data were \ndownloaded from Medline, Scopus, and Web of Science \ndatabases, while most of the data belonged to WoS and was \nconsequently used for analysis. Seventeen thousand authors \nbelonged to 135 countries and 3,900 different institutions. The \ndata were published in 1,290 different journals and got 82,879 \ncitations. The data were divided into periods, followed by the \nanalysis of period-wise publication growth. Dong et al. [8] made a bibliometric analysis of Alzheimer’s \ndisease worldwide, particularly in China. The WoS and \nPubMed databases were selected for search with data from \n1988 to 2017. One hundred eighty-one thousand one hundred \nsixteen articles were downloaded and analyzed. According to \nthis research, 30.93% were global publications, and 95.31% \nwere from China. A total of 8,935 journals participated in the \npublication of this disease. The Neurobiology of Aging journal \npublished the most articles, with 5,206 publications. Many \norganizations worked together and sponsored 11,809 articles. Missen et al. [13] analyzed Pakistan’s social science and \nscience disciplines. Two thousand publications were \nexamined, which belong to 50 authors of different disciplines. This analysis has three levels: Research, domain, and field \nlevel. They discussed single and multiple authors of articles, \nreadability scoring, title format, publication rate, gender-wise \ncontribution of researchers, and contribution of PhD students \nin research publications. This analysis found that more \nresearch is being conducted on the science discipline than the \nsocial science discipline. It was also discovered that the \nreadability scores of authors changed with time, while the \nreadability score of science articles was higher than the social \nscience ones. Ram [9] contributed to the bibliometric analysis of \nLeishmaniasis disease. 2. LITERATURE REVIEW On the other \nhand, our research is not limited to a particular country and \ncovers more than 150 years of Polio research. Demir and Comba [5] explain in their work that Celiac \ndisease (CD) is an immune disease in which people cannot eat \ngluten because it can destroy the small intestine. They analyze \nthe publications on celiac disease and find the related trends \nabout this disease, such as top articles, journals, and countries. The data were downloaded from the Web of Science database \nbetween 1980 and 2018. It was found that 13,306 articles \nrelated to celiac disease were downloaded. The most popular \nresearch area on CD was gastroenterology hepatology (2,703, \n41.3%). They also analyze the publications during the next ten \nyears, from 2019 to 2028. The Journal of Pediatric \nGastroenterology and Nutrition was regarded as the most \nactive journal. They also made the co-citation analysis and \nterm analysis just like our research. In recent years, bibliometric analysis has been widely \nadministered to analyze and evaluate scientific research The aim of the paper by Ravi and Jeyshankaris [6] is to 1334 make a scientometrics analysis of polio research papers in \nIndia. The data were downloaded from the WoS database for \nthis purpose. The study period was quite limited (1994–2018). They found that India published 488 records on Polio; all \npublications are in English, and publishing was done in \ndifferent journals. The study tells us that India published most \nof its publications (44) in 2017. The document type was also \nanalyzed. It was found that from 488 records, 317 are articles, \nwhereas letters, proceeding papers, reviews, and meeting \nabstracts are also present. While considering the global \ncitations, it was found that 20% of records did not receive any \nglobal citations. In local citations, about half, i.e., 49.5%, did \nnot get any single local citation, while only one record had \nmore than 100 citations. Of 488 papers, 76 have single-\nauthored documents, and 73 have joint authors. The most \nproductive author is T. J. John, who has 41 publications. The \njournals contributing to this Polio research are 19. By contrast, \nour research is not limited to a particular country and contains \nmuch more papers. Furthermore, we used WoS and Scopus to \nretrieve the publications. the highest h-index (211) and citation rate (3,17,646 citations). The citation rate per paper is 1.75. 2. LITERATURE REVIEW According to WHO, Leishmaniasis is \none of the neglected diseases in the world, which has become \nmore challenging for the medical sciences. The disease has \nspread to 98 countries, which is alarming. It is caused by the \nbite of phlebotomine sandflies on humans, dogs, foxes, and \nrats. For this analysis, 39,302 articles on Leishmaniasis are \nfetched from the Scopus database. The time duration is \nselected from 1968 to 2017 (50 years). Comparing the global \npublications on Leishmaniasis with India, 2008–2017 seems \nto be the most productive years for both. In the case of India, \nit is 60.34% and globally, it is 44.64%. The USA is the most \nproductive country for Leishmaniasis research, with 7,609 \npapers (19.36%). Similarly, India was ranked fifth with 3,395 \npapers. Hirsch Index (h-index) is also calculated. The USA has Fuzzy logic resolved many problems in the research areas \nand various applications, like mobile computing, for data \nanalysis and cloud computing [14]. Researchers have tried to \nmake many changes in fuzzy logic within the last few decades. For analyzing fuzzy logic, 410 research publications were 1335 were collected between 1991 to 2017. downloaded from the Web of Science (WoS) database. This \nresearch answers various questions related to essential \nconcepts of hesitant fuzzy sets. Furthermore, it determines co-\nauthorship patterns, research areas of hesitant fuzzy sets, \ncontributions of countries with various research contributions, \nco-citation patterns, and the bibliographic coupling for the \ninstitution in this field. Fang et al. [21] studied climate change and tourism \ninteractions. This has been one of the most critical research \nareas in tourism during the last few years. For this analysis, \n976 documents were extracted between 1990 to 2015. Later, \nthey identified and visualized the collaboration network of the \nauthors of these publications to find the emerging trends. They \nanalyzed from their findings that publications in this area are \nconstantly increasing. The most productive authors belong to \nthe USA, Canada, and Europe. They find out the most trending \ntopics about climate, such as tourist behavior and response \ntoward the environment. Yang et al. [15] performed an analysis on hepatocellular \ncarcinoma (HCC) using magnetic resonance imaging (MRI). With the development of MRI, many articles have been \npublished. A total of 835 articles on MRI were published from \n2008 to 2017. Journal of Magnetic Resonance Imaging has the \nmost publications (79 or 9.46%). 2. LITERATURE REVIEW South Korea is the most \nactive contributor to MRI publications, with 199 publications \n(21.82%). In the top 10 co-cited authors, J. Bruix is considered \nfirst in rank with 398 citations. Forty-seven of the most \ncommon keywords were found, with microvascular invasion \nbeing the most popular during the last three years. Therefore, \npublications on HCC MRI continuously increased from 2008 \nto 2017. The extensive analysis of diverse fields showcases the \nbreadth of bibliometric research conducted across numerous \nscientific disciplines. Various health-related studies demonstrated extensive \nbibliometric analysis: Esmaeilpour-Bandboni et al. [2] \nevaluated Iranian research contributions in Radiology, while \nHossain [4] reviewed the current scientific literature on \ncoronavirus. The research on specific diseases, such as \nAlzheimer's [8] and Leishmaniasis [9], highlighted global \ntrends, top contributing countries, institutions, and prolific \nauthors. Basu et al. [12] addressed cancer's impact and the \nscientometric evaluation of herbal medicine in its treatment, \nunderscoring the increasing challenge of cancer as a global \nhealth issue. Senel and Demir [16] made a bibliometric analysis of the \narticles about religion and health between 1975 and 2016. Fields like religion and fitness have become growing areas of \nstudy, but only a few bibliometric studies have been made in \nthese fields. The WoS database found two thousand six \nhundred eighty-three research articles. The original articles \nwere 1,655, making 62.1% of the total, whereas the remaining \nare letters, books, and proceeding papers. With 1,665 \n(62.45%) publications, the USA has the highest chunk of \npublications. Cornell University was found at the top with 73 \npapers. Two thousand nine hundred seventy-three keywords \nwere considered for use (n = 253, 250, 97, 71, and 41 times). Other analyses concentrated on neglected areas, like \nColavizza et al. [3], who explored the COVID-19 Open \nResearch Dataset (CORD-19), unraveling its broader scope \nbeyond \nCOVID-19 \nstudies. Similarly, \nChandra \n[17] \nscrutinized \nthe \nevolution \nof \nentrepreneurship \nusing \nscientometric techniques. Demir and Comba [5], also shed \nlight on Celiac disease, emphasizing research trends, top \narticles, journals, countries, and co-citation analyses. Koster et \nal. [10] focused on Rotavirus, elucidating its significant impact \non diarrheal diseases. Chandra [17] explained in his article the scientometrics \ntechniques used to study the evolution of entrepreneurship \nbetween 1990 and 2013. He used a combination of topic \nmapping, author citation analysis, and co-citation analysis. Moreover, he also made a visualization graph to show the hot \nand trending topics. 2. LITERATURE REVIEW Prakash and Arumugam [18] analyze the \ngrowth of literature related to biotechnology in India between \n2002 and 2016. The Scopus database is used to analyze Indian \ncontributions to biotechnology literature. The study analyzes \nthe performance based on many parameters such as literature \npublishing trends, authorship and co-authorship patterns, \ncollaboration patterns, top journals by the scientists and \naccording to the number of citations. The number of articles \npublished from 2002–2016 is 5,514. The trend is going upward \naccording to the number of published papers. Multiple studies employed scientometric tools and \ndatabases, such as Web of Science, Scopus, and PubMed, to \nclarify publication patterns, collaborations, and citation \nanalyses. These varied analyses collectively contribute to the \nexpanding knowledge and comprehension of diverse scientific \ndisciplines, guiding future research directions and informing \ndecision-making processes across different fields of study. 3. METHODOLOGY The present study uses a bibliometric method to analyze the \nliterature on Polio. The idea is to analyze and measure the \nscientific literature related to Polio. Quantitative, qualitative, \nand computational methods are used by bibliometrics. The \nprimary purpose of this study is to map institutional \nproductivity and the institutional ranking by research area and \njournal rank while identifying the countries and authors who \ncooperated the most. This method is beneficial for visualizing \nconsequential patterns and trends in a vast body of literature \nand scientific data. It allows the researchers to make literature-\nrelated inventions that are challenging through any other \nanalysis. The research methodology comprised data collection, \ntools and techniques, and bibliometric techniques. Kullenberg and Kasperowski [19] stated that citizen science \ninvolves the public in research to improve scientific \nknowledge. This study obtained two data sets (N=1,935, \nN=633) from the WoS database. The results reveal that there \nwere three main points. First, the citizens used different \nmethodologies for collecting and classifying data. Second, the \ncitizens are involved in collecting the geographical data. Third \nincludes public participation related to environmental and \nhealth issues. In another paper, Moraes et al. [20] showed that Mercury \n(Hg) has a hazardous effect on humans and wildlife. Because \nof its high toxic capacity in food, mercury is classified as a \npersistent toxic substance (PTS). It is obtained from natural \nsources and enters the environment from anthropogenic \nsources. Amazon rain forests are relevant in this regard on a \nglobal scale. Scientometrics analysis was applied to find out \nabout the latest trends of publications on mercury. The data The selection of WoS and Scopus databases as search \nengines was based on their widespread recognition and \nestablished prominence in the analysis of scientific literature \n[22]. Furthermore, they are well-known index databases for 1336 publications remained. This data contains articles, book \nchapters, proceeding papers, letters, and notes. It is observed \nthat these articles were written in many different languages, \nsuch as English, French, Spanish, German, Portuguese, \nJapanese, and Chinese (Complete details about document \ntypes and languages of articles are described in the \nExperiments section). Table 1 shows a detailed summary of \nthe general results. Involvement from 114 regions, 30 \nlanguages, and contributions from 4,306 institutions \ndemonstrate a widespread and diverse global engagement in \nPolio research, underscoring its international significance. This research uses quantitative analysis, graphs, and network \nmodels to visualize our findings efficiently. 3.1 Tools and techniques In total, 13390 publications on Polio were obtained, 3,635 \nfrom the Web of Science database and 9,755 from the Scopus \ndatabase. The data of these two databases was merged, \nresulting in 2,988 duplicates. After removing all the duplicates, \n10,402 publications remained. A revisit of the title and abstract \nwas done in order to ensure that the data must contain the word \nPolio. However, after revision, we found that much data was \nunrelated to our research work, and data related to different \ndiseases and viruses other than Polio was also present. Several bibliometric analysis tools exist, each with strengths \nand abilities [23]. Therefore, after thoroughly examining each \ntool, we find that the appropriate use of various tools for \nvarious types of analysis is essential. Therefore, we take an \noverview of tools like VOSviewer, Gephi, HistCite, Citespace, \nBibexcel, and Rtools. However, we find VOSviewer and \nRtools more flexible and accurate than others. 3. METHODOLOGY The flow chart of \nthis study is shown in Figure 2. The selected research papers \nare analyzed using the current acclaimed bibliometric mapping \ntools, such as VOSviewer and R-studio. the scientific literature. However, the reason for selecting \nthese databases for data extraction is the large dataset involved, \nand many previous analyses were also based on these \ndatabases. Following strict selection criteria, we collect the \nworld’s most prominent scientific and technical journals from \nboth databases. This ensures a high quality of retrieved papers \non Polio. The data were downloaded from Scopus and WoS \ndatabases using the keywords ‘Polio’ or ‘Poliomyelitis’. The keywords ‘Polio’ or ‘Poliomyelitis’ are prevalent in this \nresearch field, ensuring comprehensive coverage of related \nareas. Employing these keywords in the search process across \nthe title, abstract, and keywords sections of documents was \ncrucial. The literature search spanned from 2007 to June 2019 \nin the WoS database and from 1857 to 2019 in the Scopus \ndatabase to capture all relevant articles for the study. Figure 1. Selection process of the studies for exclusion in the \nreview Table 1. Summary of general results \n \nCriteria \nQuantity \nTime Span \n1857–2019 \nDocument type \n16 \nLanguages \n30 \nDocuments \n6,139 \nAuthors \n4,572 \nSource Journals \n1,725 \nRegions \n114 \nInstitutions \n4,306 \nCited References \n58,438 \nTerm Analysis \n10,416 \nDocuments per Author \n0.506 \n \n \nFigure 2. Research process of Polio research Table 1. Summary of general results Figure 1. Selection process of the studies for exclusion in the \nreview The year 2020 was excluded to improve the results' \naccuracy. If the most recent (incomplete) year had been \nincluded, getting the same number of documents might not be \npossible if the analysis is repeated. The reason is that several \njournal issues are released and uploaded to databases after \nseveral months of publication to be online. The search results \nare saved in BibTeX format, and the cited reference \ninformation is included. The selection criteria for inclusion are \nshown in Figure 1. Figure 2. Research process of Polio research 3.3 SCImago Journal Rank (SJR) SJR measures the scientific impact of scholarly journals that \ncount both the importance or prestige of the journals, from \nwhere the citations come from and the citations received by a \njournal. A journal’s SCImago Journal Rank shows a numeric \nvalue that indicates the average number of weighted citations \nreceived during a selected year, during the previous three years \nper document published in the journal. The higher the value of \nSJR, the greater the prestige of the journal [29]. SJR does not \nonly rank journals but countries as well. It can tell the citations \nof that journal, H-index, place of publication, editor name, \nsubject category to which certain journal belongs, scope, \ncitations per document, and documents cited. All of the \naforementioned fields are shown in graph format as well. (2) \nOverlay visualization: This visualization is the same \nas network visualization, except the items’ colors differ. In the \noverlay visualization, the items can be colored differently. In \nthe first case, the color of an item is determined by the score \nwhen the items are scored. Therefore, when the score is low, \nthe color by default is blue, and when the score is higher, it \nranges from green to yellow. If the items have no scores, then \noverlay visualization is not shown. In this research, we only \nmake one overly visualization graph to find the new and old \nterms within the given period. (2) \nOverlay visualization: This visualization is the same \nas network visualization, except the items’ colors differ. In the \noverlay visualization, the items can be colored differently. In \nthe first case, the color of an item is determined by the score \nwhen the items are scored. Therefore, when the score is low, \nthe color by default is blue, and when the score is higher, it \nranges from green to yellow. If the items have no scores, then \noverlay visualization is not shown. In this research, we only \nmake one overly visualization graph to find the new and old \nterms within the given period. (3) \nDensity visualization: In this type of visualization \ngraph [24], the items are also represented similarly to the \nnetwork and overlay visualization. Each point of the item in \ndensity visualization is represented by a color that indicates \nthe density. By default, it ranges from blue to green and green \nto yellow. 3.1.2 R (Biblioshiny) R-Studio is an integrated development environment (IDE) \ntailored for the R language, specifically designed for statistical \ncomputation and graphics [26]. R-studio provides several \npackages such as Shiny, RMarkdown, flex-dashboard, \nTidymodels, Sparklyr, Stringr, Reticulate, and Plumber. However, the Bibliometrix package of R-Studio was selected \nfor bibliometric analysis in related research. Biblioshiny is the \ninterface of bibliometrix [27]. 𝐼𝐹2018  =  \n𝐶𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠(2017) + 𝐶𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠(2016)\n𝑃𝑢𝑏𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠(2017) + 𝑃𝑢𝑏𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠(2016) \n(1) 𝐼𝐹2018  =  \n𝐶𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠(2017) + 𝐶𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑠(2016)\n𝑃𝑢𝑏𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠(2017) + 𝑃𝑢𝑏𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛𝑠(2016) \n(1) (1) It has many features that are very helpful to carry out deep \nbibliometric analysis. The interface of biblioshiny is well \nmanaged and divided according to the workflow [28]. A main \nmenu presents all data summaries, such as year span, total \nauthors, total citations, total references, and single-author and \nmulti-author documents. The analysis options are divided into \nseven categories: Overview, Sources, Authors, Documents, \nConceptual structures, Intellectual structure, and social \nstructure. The graphs that have been generated can be exported These metrics filter out top journals in a particular domain \nwherever they are needed. 3.3 SCImago Journal Rank (SJR) In this study, the analysis of the top active journals is \nconducted along with finding the SJR of 2019 and the subject \ncategory related to those journals. This analysis helps us to \nfind out which journal belongs to which specific areas of \nresearch [30] (“SJR: Scimago Journal and Country Rank”, \n2020). The weights of the neighboring items are higher when the \nitems of the neighborhood are higher in point and the color of \nthe point is yellow. On the other hand, the weights of the \nneighboring items are smaller when the neighbourhood items \nare lower in point, and the point color is blue. An academic journal's Impact Factor (IF) is a bibliometric \nindex representing the average citations received annually. Its \ncalculation involves aggregating the total citations garnered by \narticles over the last two years and dividing this by the total \nnumber of articles published within that period or a specific \ntimeframe [31]. Across academic disciplines, the IF helps in \nassessing the significance of publications or academic \ncontributions, typically considering journals with higher IF as \nmore influential. The formula to compute the IF for the year \n2018 is expressed in Eq. (1). 3.1.1 VOSviewer Therefore, we applied a filter on the title and extracted only \nPolio-related data, or applied a filter on the title and extracted \ndata that must contain the word Polio or Poliomyelitis. After \nfiltering the data, it was discovered that 4,263 publications are \nirrelevant. After excluding all the irrelevant data, 6,139 VOSviewer is a software that offers the main functionality \nrequired for visualizing, producing, and exploring bibliometric \nnetworks [24]. This idea of visualizing bibliometric networks \nreceived much attention during the early days of bibliometric \nresearch. Bibliometric network visualization has become a 1337 to several file formats; maps can be exported to Pajek and then \nfurther analyzed in VOSviewer. powerful approach to analyzing bibliometric networks in a \nlarge variety, which can depict the relationship between \nauthors and co-authors, find a relationship between countries \nand institutions or citation and co-citation networks, and also \nfind the subject category and term analysis. With time, \nresearchers have started to analyze large networks, thus \nrequiring more advanced visualization tools [25]. The \nVOSviewer (version 1.6.15) was used in this research and is \nfreely available. All the tabs that were used are described next: Similarly, the tables can be copied, downloaded, or saved as \nExcel, CSV, PDF or printed. Later, the file of Scopus and Web \nof Science literature in BibTeX format was uploaded on the \nBiblioshiny interface. As per the study's objectives, the Excel \nfiles were downloaded and used for further data analysis and \nfor making tables and graphs, as described in the next section. 3.2 Linear forecasting VOSviewer displays graphs in three ways, but we use only \nnetwork visualization and overlay visualization graphs in this \nresearch work. Forecasting is also performed in this research work. Forecasting is the technique that helps us predict the future. Linear forecasting is applied to the yearly publication growth \nof polio articles, and we forecast the number of publications \nduring the next four years. Linear forecasting is a type of time \nseries forecasting. The linear forecasting function is \ncategorized and calculated under the statistical function of \nMicrosoft Excel. It predicts a future value by using linear \nregression. (1) \nNetwork visualization: The network visualization \ngraph represents the items by labels and circles by default. The \nitem's weight determines the label's size and the item's circle. If the item's weight is more significant, its label and circle size \nare also larger. Some items whose labels are not displayed are \nalso present; this is done to avoid overlapping of labels. Their \ncluster represents the color of an item. The lines between items \ndemonstrate the links. By default, one thousand lines are \ndrawn, representing the most vital links between different \nitems. In this work, we make three network visualization \ngraphs and find the cooperation of the authors, countries, and \ninstitutions. We also perform the term analysis. (1) \nNetwork visualization: The network visualization \ngraph represents the items by labels and circles by default. The \nitem's weight determines the label's size and the item's circle. If the item's weight is more significant, its label and circle size \nare also larger. Some items whose labels are not displayed are \nalso present; this is done to avoid overlapping of labels. Their \ncluster represents the color of an item. The lines between items \ndemonstrate the links. By default, one thousand lines are \ndrawn, representing the most vital links between different \nitems. In this work, we make three network visualization \ngraphs and find the cooperation of the authors, countries, and \ninstitutions. We also perform the term analysis. 4. EXPERIMENTS AND RESULTS A comprehensive dataset spanning 162 years (1857 to 2019) \nregarding polio research publications was collected from the \nWeb of Science and Scopus databases, comprising 6,139 1338 records. This extensive dataset was analyzed using tools such \nas R-studio, Microsoft Excel, and VOSviewer to gain insights \nand visualize trends within the data. Table 3 indicates the language-wise literature output on \nPolio. Among the 6,139 papers, 85.77% were published in \nEnglish, showcasing the language's dominance in conveying \nPolio-related research. The total number of documents \npublished in languages other than English is 873, around 14.23% \nof the total publications. 4.2 Publication output trends: Analyzing growth over time Table 2 shows the document types of world contributions to \npolio research. Most of the research papers on Polio are \narticles (4,369, 71.16%), followed by reviews (411), letters \n(344) and editorials (179). Therefore, journal articles stand out \nas researchers' most favored mode of research communication. The scientific documents underwent analysis by periods, as \ndepicted in Figure 3. Publications showed an upward trend \nbeginning in 1963. Over the past three decades, there was \nconsistent growth in the average number of publications per \nperiod: 1990–1999 (95), 2000–2010 (147), and 2011–2017 \n(254). However, there was a decline in publications in 2018 \nand 2019 (n=191). Notably, the pinnacle of publications was \nobserved in 2014, reaching its peak at 340. The annual growth \nrate is 5.34%. The prediction of publication volume was \naccomplished through a statistical function utilizing linear \nregression to forecast future values. The forecast for the \nupcoming four years (including 2020) stands at 148, 149, 151, \nand 153 publications respectively. This cumulative growth \nunderscores the escalating significance of subject-related \npublications, showing an exponential increase over the years. Table 2. Distribution of document types in Polio research D\nt T\nN\nf R\nd\nP\nt Document Types \nNo. of Records \nPercentage \nArticle \n4,369 \n71.16 \nArticle in press \n18 \n0.29 \nArticle, proceedings paper \n3 \n0.04 \nBook \n87 \n1.41 \nConference paper \n87 \n1.41 \nCorrection \n12 \n0.19 \nEditorial \n179 \n2.91 \nErratum \n27 \n0.43 \nLetter \n344 \n5.60 \nMeeting abstract \n117 \n1.90 \nNews item \n79 \n1.28 \nNote \n312 \n5.08 \nPoetry \n2 \n0.03 \nReprint \n2 \n0.03 \nReview \n411 \n6.69 \nShort survey \n90 \n1.46 \nTable 3. Language-wise distribution in Polio research Figure 3. Number and accumulation of publications per year \nin Polio research Table 3. Language-wise distribution in Polio research Language \nNo. of records \nPercentage \nEnglish \n5,266 \n85.77 \nGerman \n224 \n3.64 \nSpanish \n125 \n2.03 \nFrench \n91 \n1.48 \nChinese \n63 \n1.02 \nItalian \n61 \n0.99 \nJapanese \n57 \n0.92 \nSwedish \n39 \n0.63 \nPolish \n34 \n0.55 \nDutch \n31 \n0.50 \nPortuguese \n24 \n0.39 \nRussian \n24 \n0.39 \nDanish \n21 \n0.34 \nRomanian \n18 \n0.29 \nCzech \n10 \n0.16 \nNorwegian \n10 \n0.16 \nTurkish \n8 \n0.13 \nFinnish \n5 \n0.08 \nHungarian \n5 \n0.08 \nHebrew \n4 \n0.06 \nPolyglot \n3 \n0.04 \nSlovak \n3 \n0.04 \nBulgarian \n2 \n0.03 \nCroatian \n2 \n0.03 \nGreek \n2 \n0.03 \nKorean \n2 \n0.03 \nSerbian \n2 \n0.03 \nArabic \n1 \n0.01 \nBosnian \n1 \n0.01 \nThai \n1 \n0.01 Figure 3. Number and accumulation of publications per year \nin Polio research 4.3 Authors and their cooperation Twelve thousand one hundred twenty-four different authors \nwrote the 5,781 publications. Three hundred fifty-eight \npublications are without an author name. Most authors (71.3%; \nn=8,290) are associated with a single publication, while 14.6% \n(n=1,775) are credited in two, 5.2% in three, 2.5% in four, and \n6.2% in five or more. Table 4 highlights the top ten most \nprolific authors based on their total number of publications. The analysis of key authors in Polio research reveals a blend \nof significant contributors from various countries, notably \nSwitzerland and the USA. Notably, R. Sutter emerges as both \nthe most productive and cited author. The USA maintains a \nnotable presence among top authors, with individuals like M. Pallansch, K. Thompson, and S. Cochi contributing \nsignificantly in volume and average citations per publication. 1339 Table 4. Top 10 most-productive authors in Polio research Table 4. Top 10 most-productive authors in Polio research Authors \nCountry \nPublications \nCitations \nAvg. Citations \nPub. as the 1st Author \nSutter, R. Switzerland \n109 \n4042 \n37 \n11 \nPallansch, M. USA \n93 \n3975 \n42.7 \n2 \nThompson, K. USA \n72 \n1854 \n25.7 \n27 \nJohn, T. India \n61 \n792 \n12.9 \n36 \nOberste, M. USA \n60 \n1254 \n20.9 \n2 \nWassilak, S. Europe \n59 \n1571 \n26.6 \n5 \nKew, O. USA \n54 \n3446 \n63.8 \n9 \nCochi, S. USA \n52 \n1655 \n31.8 \n9 \nAylward, R. Switzerland \n50 \n1511 \n30.2 \n10 \nDuintjer, T.R. USA \n47 \n1147 \n24.4 \n25 Table 5. Top 10 most-active journals in Polio research Table 5. Top 10 most-active journals in Polio research \n \nJournal Title \nPubl. 4.3 Authors and their cooperation SJR \n2019 \nImpact \nFactor \n2019 \nSubject Category (SJR) \nVaccine \n245 \n1.683 \n4.76 \nBiochemistry: Genetics and Molecular Biology, \nMolecular Medicine, \nImmunology and Microbiology: Immunology and Microbiology (miscellaneous), \nMedicine: Infectious Diseases, Public Health, Environmental and Occupational \nHealth, Veterinary: Veterinary (misc.) \nJournal of Infectious \nDiseases \n188 \n2.946 \n4.71 \nMedicine: Immunology and \nAllergy Infectious Diseases \nIndian Pediatrics \n114 \n0.285 \n1.163 \nMedicine: Pediatrics, Perinatology and Child Health \nScience \n89 \n13.11 \n41.037 \nArts and Humanities: History and Philosophy of Science, \nMultidisciplinary: Multidisciplinary \nBulletin of the \nWorld \nHealth Organization \n72 \n2.502 \n6.818 \nMedicine: Public Health, Environmental and \nOccupational Health \nArchives of \nPhysical Medicine \nand Rehabilitation \n70 \n1.114 \n2.697 \nHealth Professions: Physical Therapy, Sports Therapy \nand Rehabilitation, \nSports Science Medicine: Rehabilitation \nThe Lancet \n62 \n14.554 \n59.102 \nMedicine: Medicine (miscellaneous) \nDeutsche \nMedizinische \nWochenschrift \n61 \n0.176 \n0.15 \nMedicine: Medicine (miscellaneous) \nBritish Medical \nJournal \n59 \n2.049 \n27.604 \nMedicine: Medicine (miscellaneous) \nNature \n59 \n14.047 \n43.07 \nMultidisciplinary: Multidisciplinary The average number of publications per author is 0.506. The \nauthor's name is missing in 5.8% (n=358/6,139) of the \npublications. Sixty-three publications do not have a specific \nauthorship. 29.3% (n=1,801) of the publications have single \nauthorship. Out of the publications analyzed, 14.2% (n=874) \ninvolved two authors, 12.2% (n=749) had three authors, 9.2% \n(n=565) had four authors, 6.9% (n=423) had five authors, and \n21.3% (n=1,306) had six or more authors, with a maximum of \n15 authors per publication. The authors' collaborative patterns \nin publishing were examined using VOSviewer, as shown in \nFigure 4. The size of the circles indicates the publication \nvolume, while the curved connections represent collaborative \nties. The colors denote distinct collaboration clusters within \nthe network, identifying 27 author clusters. (5.5%) contributed significantly by publishing 11 or more \narticles, with publication counts ranging from 11 to 245. Table \n5 outlines details regarding the top 10 most active journals. These ten journals accounted for 16.5% of all publications \n(n=1019 out of 6,139). According to the Scimago Journal \nRanking (SJR), the primary sub-area category for these most \nrecurring journals falls under Medicine: Infectious Diseases. Journals like \"Vaccine\" and \"Journal of Infectious Diseases\" \ndemonstrate strong relevance to Polio research, focusing on \nImmunology, Infectious Diseases, and Pediatrics. Other \ninfluential journals such as \"Science,\" \"The Lancet,\" and \n\"Nature\" cover broader multidisciplinary areas, indicating \ntheir significant influence beyond specific medical domains. These results reflect a comprehensive landscape, from \nspecialized \nmedical \npublications \nto \nmultidisciplinary \nplatforms, emphasizing the diverse avenues for Polio-related \nresearch dissemination and impact. 4.4 Journals publishing on Polio research Out of the 6,139 published articles, they were distributed \nacross 1,725 journals. Among these journals, 1,011 (58.6%) \nwere responsible for publishing only one article each. 283 \n(16.4%) journals published two articles. One hundred nine \n(6.3%) published three articles. Similarly, 227 (13.1%) \njournals published four to ten articles. Among the journals, 95 Figure 5 demonstrates the publication frequency for the top \nfive most influential journals over the years. There has been a \nnoticeable rise in publications during the past decade. The \nsubstantial volume of publications in both ‘Vaccine’ and \n‘Journal of Infectious Diseases’ can be attributed to including \nconference proceedings and editorials. 1340 Figure 4. Author cooperation network in Polio research the USA emerged as the leading producer of publications in \nthis domain. Figure 6. Distribution of publications across countries or \nterritories in Polio research Figure 4. Author cooperation network in Polio research Figure 6. Distribution of publications across countries or \nterritories in Polio research Figure 5. Frequency of publications across years in the top \nfive most influential journals Figure 5. Frequency of publications across years in the top \nfive most influential journals Figure 7 showcases the top 10 countries and territories with \nthe most publications. There was no publication in the journal \nfrom 1857 to 2017. Therefore, these years were skipped from \nthe graph. Economically developed countries significantly \ncontribute to scientific and academic advancements. The top \n10 most productive countries in polio publications include the \nUSA, India, United Kingdom, Sweden, Germany, France, \nNetherlands, Switzerland, Italy, and Pakistan. Information \nfrom countries and territories' affiliations of the authors is \npresent in 6,417 publications. Figure 7. Countries and territories leading in publication \nproductivity: Top 10 Rankings Figure 5. Frequency of publications across years in the top \nfive most influential journals 4.5 Geographical and institutional distribution, along with \ncollaborative partnerships of \nPublications \nWorld Health Organization \nSwitzerland \n371 \nCenters for Disease Control \nand Prevention \nUSA \n202 \nBill and Melinda Gates \nFoundation \nUSA \n64 \nNational Center for \nImmunization and Respiratory \nDiseases \nUSA \n64 \nCenter for Global Health \nUSA \n52 \nStatens Serum Institute \nDenmark \n50 \nInstitute Pasteur \nFrance \n48 \nLund University \nSweden \n46 \nUniversity of Amsterdam \nAmsterdam \n41 \nLondon School of Hygiene and \nTropical Medicine \nLondon \n36 \n \n \n \nFigure 9. Collaboration network among institutions and \nregions Table 6. Top 10 institutions with the highest productivity to the Netherlands and Bangladesh (yellow group). The \nseventh cluster relates to India (purple group). The eighth \ncluster relates to Sweden (sky-blue group). The ninth cluster \nrelates to Pakistan (orange group). Table 6. Top 10 institutions with the highest productivity \n \nInstitution \nCountry \nNo. of \nPublications \nWorld Health Organization \nSwitzerland \n371 \nCenters for Disease Control \nand Prevention \nUSA \n202 \nBill and Melinda Gates \nFoundation \nUSA \n64 \nNational Center for \nImmunization and Respiratory \nDiseases \nUSA \n64 \nCenter for Global Health \nUSA \n52 \nStatens Serum Institute \nDenmark \n50 \nInstitute Pasteur \nFrance \n48 \nLund University \nSweden \n46 \nUniversity of Amsterdam \nAmsterdam \n41 \nLondon School of Hygiene and \nTropical Medicine \nLondon \n36 Figure 8. Cooperation network between countries and \nregions Figure 8. Cooperation network between countries and \nregions The tenth cluster relates to Turkey (pink group). The \neleventh cluster relates to Italy (grey group). The twelfth \ncluster relates to Switzerland (light purple group). In our \nanalysis of country cooperation in publications, we found that \nthe UK collaborates significantly with Western European \ncountries. Similarly, Germany's collaborations extend notably \nto African nations. Notably, Nigeria is the sole African country \ndisplaying strong connections with the USA and the UK. Pakistan has connections with the USA, Saudi Arabia, \nAustralia, Germany, and Nigeria. The United States is a \ncentral hub in these relationships, while Japan is associated \nwith neighboring Asian countries. Figure 9. Collaboration network among institutions and \nregions Four thousand three hundred six research institutions \ncontributed to 4,617 publications for which affiliation data was \navailable (with the possibility of multiple authors per \npublication or authors affiliated with multiple institutions). To \nensure consistency, the names reported in the databases were \nstandardized across different records in Scopus and WoS. 4.5 Geographical and institutional distribution, along with \ncollaborative partnerships Each publication underwent assignment to a country based \non the available information within the author affiliations and \naddresses documented in WoS and Scopus databases. A total \nof 1,522 publications lacked any identifiable affiliation. Approximately 75.2% of the publications were associated with \na specific region or country. Publications potentially linked to \nmultiple countries or institutions were assigned multiple \naffiliations or authorships, considering all affiliations based on \ncountry or institution. Figure 7. Countries and territories leading in publication \nproductivity: Top 10 Rankings Figure 8 depicts the collaboration network among countries \nand territories in Polio research created using VOSviewer. The \nnetwork explicitly highlights countries with five or more \npublications, excluding those not interconnected. Circle sizes \ncorrespond to publication volumes, while connections signify \ncollaborative efforts between countries. The analysis identifies \nthirteen primary clusters, with the USA forming the central \ngroup, followed by the UK (peach-colored cluster) and a third \ncluster involving Ethiopia and Cuba (red-colored cluster). The \nfourth cluster relates to Japan and Brazil (green). The fifth \ncluster relates to France (blue group). The sixth cluster relates The body of publications regarding Polio originated from \n114 distinct regions worldwide. Among these, 31 are in \nEurope, 32 are in Asia, 33 are in Africa, and 15 are in the \nAmericas. Figure 6 provides a visual representation of the \nglobal distribution showcasing the contribution of these \ncountries and territories. A breakdown reveals that 67 countries or territories (58.8%) \ncontributed fewer than ten publications, while 28 (24.6%) \nproduced between 11 and 50 publications. Furthermore, 11 \n(9.6%) contributed between 51 and 150 publications. Notably, 1341 Table 6. Top 10 institutions with the highest productivity \n \nInstitution \nCountry \nNo. of \nPublications \nWorld Health Organization \nSwitzerland \n371 \nCenters for Disease Control \nand Prevention \nUSA \n202 \nBill and Melinda Gates \nFoundation \nUSA \n64 \nNational Center for \nImmunization and Respiratory \nDiseases \nUSA \n64 \nCenter for Global Health \nUSA \n52 \nStatens Serum Institute \nDenmark \n50 \nInstitute Pasteur \nFrance \n48 \nLund University \nSweden \n46 \nUniversity of Amsterdam \nAmsterdam \n41 \nLondon School of Hygiene and \nTropical Medicine \nLondon \n36 \n \n \n \nFigure 9. Collaboration network among institutions and \nregions Table 6. Top 10 institutions with the highest productivity \n \nInstitution \nCountry \nNo. 4.6 Citation analysis This section delves into how these documents are \nreferenced in other publications. The citation analysis helps \nidentify how often a publication has been referenced. Out of \nthe 6,139 publications, they were cited 58,438 times in other \npublications up to the data extraction point. This accounts for \nan average of 9.519 citations per publication. Of all the institutions involved, 71% (n=3,058) participated \nin just one publication, while 13.5% (n=580) were involved in \ntwo publications, and 13% (n=564) contributed to three \npublications. A smaller percentage, 1.6% (n=68), participated \nin 11 to 20 publications, and a mere 0.8% of institutions (36) \nwere responsible for 20 or more publications. Table 6 outlines \ndetails regarding the top 10 most productive institutions. Most \ninstitutions belong to universities, private organizations, \nresearch centers, and institutes. Institutions like WHO and the \nCenters for Disease Control and Prevention (CDC) in the USA \nemerge as essential contributors, highlighting their noteworthy \nroles in global health and disease control. g\np\np\n33.5% (n=2,057) of the articles had not been cited. 11% \n(n=678) were cited only once. 6.9% (n=424) were cited twice. 24.7% (n=1,519) were cited between 3 to 10 times. 10.7% \n(n=655) were cited between 11 to 20 times. 9.6% (n=588) of \npublications had 21 to 50 citations. 2.6% (n=162) were cited \nbetween 51 to 100 times. 0.9% (n=56) were cited up to 454 \ntimes. The average citation of the top 10 articles was 285. Table 7 enumerates the top five frequently referenced \npublications. The primary authorship of nine publications \naligns with the USA, followed by Europe. Notably, O. Kew is \nthe sole author featured twice on this list. Regarding the \nprimary topics categorized by Scimago Journal-SJR, four \njournals revolve around Medicine, while the others focus on \nMicrobiology. Among the 6,139 journals studied (1,106 of \nwhich received more than one citation), 35.9% (n=619 out of \n1,752) had no citations. Additionally, 9.9% (n=171) received \na single citation, while 26.1% (n=451) fell within the range of Additionally, academic institutions such as Lund University \nand the University of Amsterdam display active engagement \nin Polio research, highlighting the academic community's \ndedication to understanding and fighting this disease. These \ndiverse \ninstitutions \nunderscore \na \ncooperative, \nmultidisciplinary approach towards addressing Polio globally. Figure 9 shows the cooperation network between institutions \nand territories in Polio research. 1342 two to 10 citations. Furthermore, 18.2% (n=314) accrued \ncitations ranging between 11 and 50. 4.6 Citation analysis 6.2% of the journals have \naccumulated citations falling within 51 to 200. 3% (n=52) \nhave between 200 and 1,000 citations, and 0.6% (n=10) have \ncitations ranging from 1,001 to 3,415. Vaccine is the journal \nwith the highest citations, with 5.9% (n=3,415/58,437) of the \ntotal citations. The Journal of Infectious Diseases and \nArchives of Physical Medicine and Rehabilitation collectively \ngarnered 9% (n=5,301) of the total citations. This pattern \nsuggests a strong correlation between the overall publication \ncount and the most frequently referenced journals. Figure 10 \ndepicts the top five journals referenced by other articles. citation analysis serves to quantify interactions among \npublications, aiding in the analysis of their relationships. Specifically, we focus on the top 50 highly referenced articles. Figure 11 portrays the co-citation analysis created using \nVOSviewer. The nodes represent publications, and the edges \nrepresent co-citation relationships. Circle size indicates the \nextent of citation on the subject, while distance signifies the \nlevel of relationship. One can observe that most of the articles \nwere written after 1990. The visual network reveals four \ndistinct clusters, indicating topics or research areas. Notably, \nthe red cluster pertains to Polio vaccination, while the green \ngroup is associated with conditions following polio. The \nyellow and blue groups are associated with vaccination, \neradication, and symptoms, and O. Kew (2005) is highly co-\ncited. Figure 10. Journals with the highest references from other \narticles: Top five rankings \n \nIn total 4 758 references\nere sed for co citation anal sis Figure 10. Journals with the highest references from other \narticles: Top five rankings Figure 10. Journals with the highest references from other \narticles: Top five rankings \n \nIn total, 4,758 references were used for co-citation analysis. Many articles do not contain their cited references. The co-\neradication, and symptoms, and O. Kew (2005) is highly co\ncited. Figure 11. Analysis of co-citations among extensively \nreferenced sources \n \nTable 7. Most cited publications: Top 10 rankings Figure 11. Analysis of co-citations among extensively \nreferenced sources Figure 10. Journals with the highest references from other \narticles: Top five rankings Figure 10. Journals with the highest references from other \narticles: Top five rankings In total, 4,758 references were used for co-citation analysis. Many articles do not contain their cited references. The co- In total, 4,758 references were used for co-citation analysis. Many articles do not contain their cited references. The co- Figure 11. Analysis of co-citations among extensively \nreferenced sources Table 7. 5. CONCLUSION The present study examined the polio research output \npublished from 1857 to 2019, merging Web of Science and \nScopus databases. It is observed that the publications have had \na steady growth in this field till 2014, which was also observed \nas a peak year for publications. However, after 2014, the \nnumber of publications decreased. In forecasting, it is also \nnoticed that the number of publications declined in polio \nresearch. The primary reason for this decline is that according \nto WHO, the entire world except Pakistan and Afghanistan is \npolio-free. It was analyzed that 6,139 documents were \npublished in Polio during 162 years. Twelve thousand one \nhundred twenty-four authors participated in publications in \nthirty languages, 1,725 journals, and sixteen document types. The most contributed country in polio publications is the USA. One hundred fourteen regions participated with 4,306 \ninstitutions. For the 6,139 publications, a total of 58,438 \ncitations were received. The author of the most cited \npublication was O. Kew in 2005, and the most cited journal is \n‘Vaccine’. A total of 4,758 co-cited references were also found. In term analysis, the most repeated words are ‘polio’ and \n‘Poliomyelitis’. Figure 12. Terms analysis Figure 12. Terms analysis In conclusion, these results provide an idea for future \nresearchers of Polio to analyze the current scientific literature \nand fill the gaps in the field for further research. Furthermore, \nresearchers in developing countries like Pakistan need to \nundertake research in polio and its related fields to make such \ndeveloping countries polio-free. The current research \nunderscores the importance of future investigations focusing \non unexplored aspects, including the long-term effects of polio, \naddressing vaccine hesitancy, and exploring socio-economic \nimpacts. Identifying and bridging gaps in cultural implications, \ndemographic impacts, and post-eradication challenges remain \ncritical. Encouraging global collaboration, particularly from \nregions that have eradicated polio, is vital for sustaining \nprogress and redirecting research efforts toward public health \ninitiatives. This study advocates for ongoing research in \ndeveloping countries to sustain polio-free status. It suggests Figure 13 depicts the temporal relationship among terms, \nshowcasing the average publication period represented by the \ncolor of the terms. This average is computed from the \ncollective publication years of all associated publications. The \nspectrum spans from 1990 to 2019, with yellow denoting \nnewer terms and blue indicating older ones. The prominence \nof terms, delineated by the color range and circle size, \nhighlights the prevalence of terms predominantly between \n2000 and 2010. 4.6 Citation analysis Most cited publications: Top 10 rankings Table 7. Most cited publications: Top 10 rankings Title \nReferences \nCountry \nInstitution \nJournal-IF \nSJR (2018-2019) \nTimes \nCited \nAvg. Cit. per \nYear \nMain Topic \n(Category SJR) \nVaccine derived \npolioviruses and the \nendgame strategy for \nglobal polio eradication \nKEW O \n2005 \nUSA \nNational Center \nfor Infectious \nDiseases \nAnnual Review of \nMicrobiology \n(5.62-6.517) \n454 \n28.38 \nMicrobiology \nOutbreak of poliomyelitis \nin Hispaniola associated \nwith circulating type 1 \nvaccine derived \npoliovirus \nKEW O \n2002 \nUSA \nNational Center \nfor Infectious \nDiseases \nScience \n(41.037-13.11) \n423 \n22.26 \nHistory and \nPhilosophy of \nScience \nA long-term follow-up \nstudy of patients with \npost poliomyelitis \nneuromuscular symptoms \nDALAKAS \nMC \n1986 \nUSA \nNational Institute \nof Neurological \nNew England \nJournal \nof Medicine \n(70.670-18.291) \n291 \n8.31 \nMedicine \n(miscellaneous) \nLymphoblastic leukemias \nevidence for the \ninvolvement \nof the polio virus receptor \ncd 155 and nectin2 cd 112 \nPENDE D \n2005 \nEurope \nIstituto \nNazionale \nper la Ricerca sul \nCancro \nBlood \n(16.601-5.416) \n268 \n16.75 \nBiochemistry, Cell \nBiology, \nImmunology, \nMedicine \nA protein covalently \nlinked to poliovirus \ngenome RNA \nUSA \nLEE YF \n1977 \nState University \nof New York \nPNAS \n(9.58-5.165) \n254 \n5.77 \nMultidisciplinary 1343 Lund University and the University of Amsterdam collectively \nspearhead \nPolio \nresearch, \nshowcasing \na \nunited, \ninterdisciplinary effort toward eradicating global disease. 4.7 Analysis of terms The examination of terms present in the publications offers \ninsights into primary subjects and evolving research directions. The terms frequently appearing together in different document \nparts are often considered related. This analysis measures the \nstrength of the association using the frequency of the co-\noccurrence in titles, keywords, and abstracts. Terms occurring \nin at least ten publications were considered, resulting in the \nselection of 662 terms for inclusion in the network. The \noutcomes of this term analysis are depicted in Figure 12, where \ncircles denote term occurrences, and the distance between \nthem signifies their relation. The frequency of their co-\noccurrence indicates relationships among terms. The analysis \nidentified six distinct clusters, notably highlighting a red \ncluster associated with Immunization (disease eradication, \nprevention, developing countries). Countries affected by Polio \nare also indicated (Afghanistan, Africa, Australia, Europe, \nIndia, and Pakistan). The green cluster is related to humans, \npost poliomyelitis syndrome, symptoms, females, children, \nand age groups. The blue cluster represents the poliomyelitis \nvirus, polio virus, and virus antibody. The yellow cluster \nrelates to the poliomyelitis vaccine, oral vaccination, and \nvarious circumstances. The purple cluster represents all the \nterms related to polio. The most frequent words are Polio, \npoliomyelitis, poliomyelitis vaccination, children, eradication, \nclinical condition, paralysis, and developing countries. Figure 13. Analysis of Terms with Temporal Data Figure 13. Analysis of Terms with Temporal Data The WHO and CDC, USA, and academic powerhouses like REFERENCES [15] Yang, D.W., Wang, X.P., Wang, Z.C., Yang, Z.H., Bian, \nX.F. (2019). A scientometric analysis on hepatocellular \ncarcinoma magnetic resonance imaging research from \n2008 to 2017. 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