scholarly journals Bibliometric Analysis Of Sustainable And Green Consumption Research From 1974 To 2019

2021 ◽  
Vol 12 (5) ◽  
pp. 1292-1301
Author(s):  
Nornajihah Nadia Hasbullah, Et. al.
Keyword(s):  
Bibliometric Analysis ◽  
Environmental Concern ◽  
Sustainable Consumption ◽  
Strong Support ◽  
The United States ◽  
Systematic Analysis ◽  
Total Citation ◽  
Green Consumption ◽  
Network Analyses ◽  
Consumer Marketing

The past decade witnessed the resurgence of sustainable consumption due to the strong support offered by companies, consumers, institutions, and society. Nevertheless, examination of sustainable consumption via bibliometric and network analyses is absent from the vast literature. In order to bridge this gap, a bibliometric analysis was performed on all publications related to sustainable consumption in the Scopus database for the period of 1974-2019. Upon analyzing 2352 articles, several parameters were determined, namely the trends in publications, the most popular journals, the productive countries of the most important countries, most of the studies cited and the list of keywords for further description (psychosocial factors).From the selected 160 journals, articles were most-frequently published in Sustainability Switzerland, while the Journal of Consumer Marketing ranked first for total citation. The emergence of sustainable consumption topic was spread across 120 countries and 159 academic institutions. This present study discovered that the United States dominated publication production, whereas Universität Göttingen in Germany was the most productive institution. Upon further systematic analysis using VOS viewer, 5333 keywords were listed. The top four clusters of psychosocial determinants were discussed in light of social norm, attitude, environmental concern, and perceived value. Building on the outcomes retrieved from this analysis, researchers may better plan their studies and contribute better insights of their empirical investigations.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals Osteopathic empirical research: a bibliometric analysis from 1966 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chantal Morin ◽  
Isabelle Gaboury
Keyword(s):  
Bibliometric Analysis ◽  
Empirical Research ◽  
Scientific Literature ◽  
Case Reports ◽  
Empirical Studies ◽  
Body Part ◽  
The United States ◽  
Mesh Terms ◽  
Research Designs ◽  
System Body

Abstract Background Despite the increasing use of osteopathy, a manipulative complementary and alternative medicine therapy, in the general population, its efficacy continues to be debated. In this era of evidence-based practice, no studies have previously reviewed the scientific literature in the field to identify published knowledge, trends and gaps in empirical research. The aims of this bibliometric analysis are to describe characteristics of articles published on the efficacy of osteopathic interventions and to provide an overall portrait of their impacts in the scientific literature. Methods A bibliometric analysis approach was used. Articles were identified with searches using a combination of relevant MeSH terms and indexing keywords about osteopathy and research designs in MEDLINE and CINAHL databases. The following indicators were extracted: country of primary author, year of publication, journals, impact factor of the journal, number of citations, research design, participants’ age group, system/body part addressed, primary outcome, indexing keywords and types of techniques. Results A total of 389 articles met the inclusion criteria. The number of empirical studies doubled every 5 years, with the United States, Italy, Spain, and United Kingdom being the most productive countries. Twenty-three articles were cited over 100 times. Articles were published in 103 different indexed journals, but more than half (53.7%) of articles were published in one of three osteopathy-focused readership journals. Randomized control trials (n = 145; 37.3%) and case reports (n = 142; 36.5%) were the most common research designs. A total of 187 (48.1%) studies examined the effects of osteopathic interventions using a combination of techniques that belonged to two or all of the classic fields of osteopathic interventions (musculoskeletal, cranial, and visceral). Conclusion The number of osteopathy empirical studies increased significantly from 1980 to 2014. The productivity appears to be very much in sync with practice development and innovations; however, the articles were mainly published in osteopathic journals targeting a limited, disciplinary-focused readership.

scholarly journals Cyber Terrorism and Public Support for Retaliation – A Multi-Country Survey Experiment

2021 ◽  
pp. 1-19
Author(s):  
Ryan Shandler ◽  
Michael L. Gross ◽  
Sophia Backhaus ◽  
Daphna Canetti
Keyword(s):  
Television News ◽  
Public Support ◽  
Strong Support ◽  
The United States ◽  
Randomized Experiments ◽  
Cyber Terrorism ◽  
News Reports ◽  
Terror Attacks ◽  
Psychological Mechanisms ◽  
Psychological Mechanism

Abstract Does exposure to cyber terrorism prompt calls for retaliatory military strikes? By what psychological mechanism does it do so? Through a series of controlled, randomized experiments, this study exposed respondents (n = 2,028) to television news reports depicting cyber and conventional terror attacks against critical infrastructures in the United States, United Kingdom and Israel. The findings indicate that only lethal cyber terrorism triggers strong support for retaliation. Findings also confirm that anger bridges exposure to cyber terrorism and retaliation, rather than psychological mechanisms such as threat perception or anxiety as other studies propose. These findings extend to the cyber realm a recent trend that views anger as a primary mechanism linking exposure to terrorism with militant preferences. With cyber terrorism a mounting international concern, this study demonstrates how exposure to this threat can generate strong public support for retaliatory policies, depending on the lethality of the attack.

scholarly journals Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals

2021 ◽  
Vol 13 (14) ◽  
pp. 7555
Author(s):  
Raghu Raman ◽  
Ricardo Vinuesa ◽  
Prema Nedungadi
Keyword(s):  
United States ◽  
Sustainable Development ◽  
Bibliometric Analysis ◽  
Data Access ◽  
Well Being ◽  
Good Health ◽  
The United States ◽  
Social Sciences And Humanities ◽  
Semantic Associations ◽  
Number Of Publications

India is ranked fifth in the world in terms of COVID-19 publications accounting for 6.7% of the total. About 60% of the COVID-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometric analysis of the publication trends and citation structure along with the identification of major research clusters. By performing network analysis of authors, citations, institutions, keywords, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by the United States, China, UK, Italy, India in COVID-19 research may be attributed to the high prevalence of COVID-19 cases in those countries witnessing the first outbreak and also due to having access to COVID-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. A large number of publications and citations from India are due to co-authored publications with countries like the United States, UK, China, and Saudi Arabia. Findings show health sciences have the highest number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open-access category. With India as the focus, by comparing three major pandemics—SARS, MERS, COVID-19—from a bibliometrics perspective, we observe much broader involvement of authors from multiple countries for COVID-19 studies when compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable development-related studies from the COVID-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding of how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in the closure of scientific institutions for an extended time.

scholarly journals A Bibliometric Analysis of the Global Trend of Using Alginate, Gelatine, and Hydroxyapatite for Bone Tissue Regeneration Applications

Polymers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 647
Author(s):  
Mohamed Saiful Firdaus Hussin ◽  
Aludin Mohd Serah ◽  
Khairul Azri Azlan ◽  
Hasan Zuhudi Abdullah ◽  
Maizlinda Izwana Idris ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Bone Tissue Engineering ◽  
Bone Tissue ◽  
Bibliometric Analysis ◽  
Research Work ◽  
The United States ◽  
Research Area ◽  
Bone Tissue Regeneration ◽  
Future Research ◽  
Starting Point

Collecting information from previous investigations and expressing it in a scientometrics study can be a priceless guide to getting a complete overview of a specific research area. The aim of this study is to explore the interrelated connection between alginate, gelatine, and hydroxyapatite within the scope of bone tissue and scaffold. A review of traditional literature with data mining procedures using bibliometric analyses was considered to identify the evolution of the selected research area between 2009 and 2019. Bibliometric methods and knowledge visualization technologies were implemented to investigate diverse publications based on the following indicators: year of publication, document type, language, country, institution, author, journal, keyword, and number of citations. An analysis using a bibliometric study found that 7446 papers were located with the keywords “bone tissue” and “scaffold”, and 1767 (alginate), 185 (gelatine), 5658 (hydroxyapatite) papers with those specific sub keywords. The number of publications that relate to “tissue engineering” and bone more than doubled between 2009 (1352) and 2019 (2839). China, the United States and India are the most productive countries, while Sichuan University and the Chinese Academy of Science from China are the most important institutions related to bone tissue scaffold. Materials Science and Engineering C is the most productive journal, followed by the Journal of Biomedical Materials Research Part A. This paper is a starting point, providing the first bibliometric analysis study of bone tissue and scaffold considering alginate, gelatine and hydroxyapatite. A bibliometric analysis would greatly assist in giving a scientific insight to support desired future research work, not only associated with bone tissue engineering applications. It is expected that the analysis of alginate, gelatine and hydroxyapatite in terms of 3D bioprinting, clinical outcomes, scaffold architecture, and the regenerative medicine approach will enhance the research into bone tissue engineering in the near future. Continued studies into these research fields are highly recommended.

scholarly journals Research Trends of Biodegradation of Cooking Oil in Antarctica from 2001 to 2021: A Bibliometric Analysis Based on the Scopus Database

2021 ◽  
Vol 18 (4) ◽  
pp. 2050
Author(s):  
Khadijah Nabilah Mohd Zahri ◽  
Azham Zulkharnain ◽  
Suriana Sabri ◽  
Claudio Gomez-Fuentes ◽  
Siti Aqlima Ahmad
Keyword(s):  
Bibliometric Analysis ◽  
Anthropogenic Activities ◽  
Drainage System ◽  
The United States ◽  
Waste Cooking Oil ◽  
Oil Degradation ◽  
Carcinogenic Effect ◽  
Cooking Oil ◽  
The Past ◽  
Scopus Database

In the present age, environmental pollution is multiplying due to various anthropogenic activities. Pollution from waste cooking oil is one of the main issues facing the current human population. Scientists and researchers are seriously concerned about the oils released from various activities, including the blockage of the urban drainage system and odor issues. In addition, cooking oil is known to be harmful and may have a carcinogenic effect. It was found that current research studies and publications are growing on these topics due to environmental problems. A bibliometric analysis of studies published from 2001 to 2021 on cooking oil degradation was carried out using the Scopus database. Primarily, this analysis identified the reliability of the topic for the present-day and explored the past and present progresses of publications on various aspects, including the contributing countries, journals and keywords co-occurrence. The links and interactions between the selected subjects (journals and keywords) were further visualised using the VOSviewer software. The analysis showed that the productivity of the publications is still developing, with the most contributing country being the United States, followed by China and India with 635, 359 and 320 publications, respectively. From a total of 1915 publications, 85 publications were published in the Journal of Agricultural and Food Chemistry. Meanwhile, the second and third of the most influential journals were Bioresource Technology and Industrial Crops and Products with 76 and 70 total publications, respectively. Most importantly, the co-occurrence of the author’s keywords revealed “biodegradation”, “bioremediation”, “vegetable oil” and “Antarctic” as the popular topics in this study area, especially from 2011 to 2015. In conclusion, this bibliometric analysis on the degradation of cooking oil may serve as guide for future avenues of research in this area of research.

A Bibliometric Analysis of the Top 100 Cited Papers in Retinal Detachment

2021 ◽  
pp. 247412642110073
Author(s):  
Masumi George Asahi ◽  
Haig Pakhchanian ◽  
Christine Doepker ◽  
Rahul Raiker ◽  
Ron P. Gallemore
Keyword(s):  
Retinal Detachment ◽  
Bibliometric Analysis ◽  
Pigment Epithelium ◽  
Retinal Pigment ◽  
Microscopic Analysis ◽  
The United States ◽  
Electron Microscopic ◽  
Research Areas ◽  
Science Index ◽  
Funding Agencies

Purpose: This work aimed to identify and analyze the most frequently cited articles in retinal detachment (RD). Methods: Institute for Scientific Information’s Web of Science index (Thomas Scientific) was used to identify the top 100 most cited articles on RD between 1900 and 2019. Data from the top 100 most cited articles that met inclusion criteria were analyzed based on title, citation frequency, authorship, institution, journal, year of publication, and country of origin. Results: The top 100 articles in RD were cited 88 to 480 times. Steven K. Fisher was the most cited individual, with the University of California system being the most cited organization. Sixty-four percent of the top 100 articles originated from the United States and were published in the American Journal of Ophthalmology, Ophthalmology, and Archives of Ophthalmology at frequencies of 36%, 24%, and 11%, respectively. The top funding agencies included the US Department of Health and Human Services, the National Institutes of Health, and the National Eye Institute at 29%, 28%, and 27%, respectively. The top-cited article, which assessed the role of the retinal pigment epithelium by histologic and electron microscopic analysis of RDs in eyes of owl monkeys, was by Machemer and Laqua in the American Journal of Ophthalmology. Conclusions: This bibliometric analysis provides researchers and clinicians with a detailed overview of the most cited manuscripts in RD. Such analyses may guide researchers and funding agencies on important research areas in the field.

Low Self-Control, Substance-Using Peers and Intimate Partners, Pro-Drug Use Definitions, and Inhalant Use Among Convicted Offenders in South Korea

2020 ◽  
Vol 51 (1) ◽  
pp. 128-142 ◽  
Author(s):  
Jaeyong Choi ◽  
Nathan E. Kruis
Keyword(s):  
Social Learning ◽  
South Korea ◽  
Strong Support ◽  
The United States ◽  
Self Control ◽  
Learning Mechanisms ◽  
Mediation Effects ◽  
Mediation Hypothesis ◽  
Low Self Control ◽  
The Relationship

Hirschi has repeatedly argued that the relationship between social learning variables and crime is a product of “self-selection” driven by low self-control (LSC). Akers’ has suggested that social learning mechanisms, such as affiliations with deviant individuals and acceptance of criminal definitions, can mediate the effects of LSC on crime. Interestingly, there has been little comparative work done to explore this mediation hypothesis in the realm of substance use for offender populations outside of the United States. This study helps fill these gaps in the literature by exploring the potential mediation effects of social learning variables on the relationship between LSC and inhalant use among a sample of 739 male offenders in South Korea. Our results provide strong support for the mediation hypothesis that LSC indirectly influences self-reported inhalant use through social learning mechanisms.

scholarly journals The Communicative Constitution of Hate Organizations Online: A Semantic Network Analysis of “Make America Great Again”

2018 ◽  
Vol 4 (3) ◽  
pp. 205630511879076 ◽  
Author(s):  
Sean M. Eddington
Keyword(s):  
Semantic Network ◽  
The United States ◽  
Political Organization ◽  
White Supremacist ◽  
Far Right ◽  
Network Analyses ◽  
The United Kingdom ◽  
White Supremacists ◽  
Media Systems ◽  
Communicative Constitution

In the context of the 2016 U.S. Presidential Election, President Donald Trump’s use of Twitter to connect with followers and supporters created unprecedented access to Trump’s online political campaign. In using the campaign slogan, “Make America Great Again” (or its acronym “MAGA”), Trump communicatively organized and controlled media systems by offering his followers an opportunity to connect with his campaign through the discursive hashtag. In effect, the strategic use of these networks over time communicatively constituted an effective and winning political organization; however, Trump’s political organization was not without connections to far-right and hate groups that coalesced in and around the hashtag. Semantic network analyses uncovered how the textual nature of #MAGA organized connections between hashtags, and, in doing so, exposed connections to overtly White supremacist groups within the United States and the United Kingdom throughout late November 2016. Cluster analyses further uncovered semantic connections to White supremacist and White nationalist groups throughout the hashtag networks connected to the central slogan of Trump’s presidential campaign. Theoretically, these findings contribute to the ways in which hashtag networks show how Trump’s support developed and united around particular organizing processes and White nationalist language, and provide insights into how these networks discursively create and connect White supremacists’ organizations to Trump’s campaign.

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