scholarly journals Scientometric analysis of psychological interventions based upon the use of Hypnosis

2017 ◽  
Vol 9 (1) ◽  
pp. 85-94
Author(s):  
Miguel Angel Muñoz
Keyword(s):  
Solid Support ◽  
The Other ◽  
Future Research ◽  
Scientometric Analysis ◽  
Psychological Interventions ◽  
Therapeutic Technique ◽  
Emotion Control ◽  
Behavioral Techniques ◽  
Fear And Anxiety ◽  
Scientometric Study

Hypnosis is a therapeutic technique that has developed for centuries, and every time with greater clinical and scientific weight. Currently, hypnosis constitutes a solid support method for treatments against chronic pain and for emotion control under situations that generate fear and anxiety -such as surgery or other type of phobias-, so it is presented as an alternative to the use of medicine/drugs by health specialists. On the other hand within the field of behavioral sciences, apart from controlling fear and anxiety responses, hypnosis serves as support to the various cognitive behavioral techniques by facilitating their assimilation and development. This work presents a scientometric study of the research done on hypnosis over the last fifteen years, from publications -in Spanish and English- in specialized journals, indexed in SCOPUS (a specialized international bibliometric database). The contemporary applications of hypnosis are presented and critically discussed; as well as the fields in which its application has proven successful; its limitations; the research networks generated within the time of the study; plus, probable projections for future research are also mentioned. 

scholarly journals Global Research Trends on the Use of Nanotechnology to Boost Meat Production: A Scientometric Analysis

2022 ◽  
Vol 6 ◽  
Author(s):  
Emrobowansan Monday Idamokoro ◽  
Yiseyon Sunday Hosu
Keyword(s):  
Research Work ◽  
Research Direction ◽  
Future Research ◽  
Meat Production ◽  
Scientometric Analysis ◽  
Annual Growth Rate ◽  
Total Citation ◽  
Production Research ◽  
Work Done ◽  
Scientometric Study

Meat production plays a vital socioeconomic role for sustainable development and for promoting food security in most countries. However, not much is known about research agendas done globally and the advancement of knowledge-generating networks in this area of study. The present study aims to reveal and analyze scientific research outputs on meat production linked with recent nanotechnology research work done till date. A compilation of research advancement and development within the sphere was realized through a scientometric study to comprehend the trend of research outputs, scientific impacts, authors' involvement, collaboration networks, and the advancement of knowledge gaps for future research endeavors on the current subject matter. Scholarly published articles were retrieved from the web of science (WOS) and Scopus databases from 1985 to 2020 and they were merged together using bibliometric package in R studio. All duplicated articles (438) from both data bases were excluded. A combination of terms (nano* AND (livestock* OR meat* OR beef* OR mutton* OR pork* OR chevon* OR chicken* OR turkey*)), and conversely analyzed for scientometric indices. A collection of 656 peer-reviewed, research articles were retrieved for the study period and authored by 2,133 researchers with a collaboration index of 3.31. The research outputs were highest in the year 2020 with total research outputs of 140 articles. The topmost three authors' keywords commonly used by authors were nanoparticles, meat, and chitosan with a respective frequency of 75, 62, and 57. China, Iran, and India ranked top in terms of meat production research outputs linked to nanotechnology and total citation with respective article productivity (total citations) of 160 (3,193), 111 (1,765), and 37 (552). Our findings revealed an increasing trend in research (with an annual growth rate of 25.18%) tending toward advancing meat production with the use of nanotechnology. Likewise, there is an increasing pointer to the fact that research work on nanotechnology and meat production has the prospect to influence positively, decision-making on research direction, and collaborations, hereby increasing the production of meat and its products in the future.

Trend Linking of Multiple System Atrophy : A Scientometric Study

2020 ◽  
Vol 20 ◽  
Author(s):  
Mahdiyeh Khazaneha ◽  
Farideh Osareh ◽  
Kaveh Shafiee
Keyword(s):  
Mesh Term ◽  
Research Field ◽  
Future Research ◽  
Collaboration Network ◽  
Scientometric Analysis ◽  
Citation Score ◽  
Common Process ◽  
Chronological Period ◽  
Descriptive Survey ◽  
Scientometric Study

Aim: To add to previous analyses and describe the trends in MSA research from three decades, 1988 to 2018, through assessing the medical literature. Additionally, a collaboration network was analyzed to determine the most common process in development of MSA research. Methods: This research was a descriptive survey with a scientometric approach. The data for the present study were collected from the Web of Science (WoS) and search strategy based on Medical Subject Heading (MeSH) term. In this research, the data analysis was performed based on collaboration network and theme analysis. Results and Conclusion: In this study, 6530 articles were retrieved from 1988 to 2018 in three different periods. These articles were drafted by 39,184 authors, 3,865 organizations, 80 countries, and 832 journals. Further, 287 articles with more than 100 citations were found. The global citation score (GCS) was 250,834 times and the average cited times per articles was reported as 3,841. The MSA research field demonstrated a diagram for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. Scientometric analysis of the field of MSA can be regarded as a roadmap for future research and policymaking in this important area.

Children With Intellectual Disability and Victimization: A Logistic Regression Analysis

2021 ◽  
pp. 107755952199417
Author(s):  
Katherine R. Brendli ◽  
Michael D. Broda ◽  
Ruth Brown
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Intellectual Disability ◽  
Logistic Regression Analysis ◽  
District Of Columbia ◽  
The Other ◽  
Future Research ◽  
Common Assumption ◽  
Research And Practice ◽  
Demographic Correlates

It is a common assumption that children with disabilities are more likely to experience victimization than their peers without disabilities. However, there is a paucity of robust research supporting this assumption in the current literature. In response to this need, we conducted a logistic regression analysis using a national dataset of responses from 26,572 parents/caregivers to children with and without disabilities across all 50 states, plus the District of Columbia. The purpose of our study was to acquire a greater understanding of the odds of victimization among children with and without intellectual disability (ID), while controlling for several child and parent/adult demographic correlates. Most notably, our study revealed that children with ID have 2.84 times greater odds of experiencing victimization than children without disabilities, after adjusting for the other predictors in the model. Implications for future research and practice are discussed.

scholarly journals A taxonomy of antonymy in Arabic: Egyptian and Saudi proverbs in comparison

2021 ◽  
Vol 7 (1) ◽  
pp. 200-222
Author(s):  
Hamada Hassanein ◽  
Mohammad Mahzari
Keyword(s):  
Main Clause ◽  
The Other ◽  
Subordinate Clause ◽  
Future Research ◽  
Case Marking ◽  
News Discourse ◽  
Discourse Functions ◽  
Syntactic Frames

Abstract This study has set out to identify, quantify, typify, and exemplify the discourse functions of canonical antonymy in Arabic paremiography by comparing two manually collected datasets from Egyptian and Saudi (Najdi) dialects. Building upon Jones’s (2002) most extensive and often-cited classification of the discourse functions of antonyms as they co-occur within syntactic frames in news discourse, the study has substantially revised this classification and developed a provisional and dynamic typology thereof. Two major textual functions are found to be quantitatively significant and qualitatively preponderant: ancillarity (wherein an A-pair of canonical antonyms project their antonymicity onto a more important B-pair) and coordination (wherein one antonym holds an inclusive or exhaustive relation to another antonym). Three new functions have been developed and added to the retrieved classification: subordination (wherein one antonym occurs in a subordinate clause while the other occurs in a main clause), case-marking (wherein two opposite cases are served by two antonyms), and replacement (wherein one antonym is substituted with another). Semicanonical and noncanonical guises of antonymy are left and recommended for future research.

scholarly journals A Scientometric Study on Industrial Effluent and Sludge Toxicity

Toxics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 176
Author(s):  
Amid Mostafaie ◽  
Diogo N. Cardoso ◽  
Mohammadreza Kamali ◽  
Susana Loureiro
Keyword(s):  
Industrial Wastewater ◽  
Web Of Science ◽  
Industrial Effluent ◽  
Toxicity Assessment ◽  
Complex Compounds ◽  
Treated Wastewater ◽  
Scientometric Analysis ◽  
Water Medium ◽  
Before And After ◽  
Scientometric Study

The growth of industrialization has led to an increase in the production of highly contaminated wastewater. Industrial wastewater contains highly complex compounds varying in characteristics and required to be treated before its discharge into a water medium from various industries. However, the efficiency of the treated wastewater from the toxicity reduction perspective is unclear. In order to overcome this barrier, toxicity assessment of the industrial wastewater before and after treatment is crucial. Thus, in this study, a scientometric analysis has been performed on the toxicity assessment of industrial wastewater and sludges, which have been reported in the literature. Web of Science (WoS) core collection database has been considered the main database to execute this analysis. Via the search of pre-researched keywords, a total number of 1038 documents were collected, which have been published from 1951 to 2020. Via CiteSpace software and WoS analyser, these documents went under analysis regarding some of the scientometry criteria, and the detailed results obtained are provided in this study. The total number of published documents on this topic is relatively low during such a long period of time. In conclusion, the need for more detailed contributions among the scientific and industrial communities has been felt.

scholarly journals Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)

2019 ◽  
Vol 11 (13) ◽  
pp. 3716 ◽  
Author(s):  
Yingling Shi ◽  
Xinping Liu
Keyword(s):  
Web Of Science ◽  
Green Building ◽  
Development Trend ◽  
Status Quo ◽  
Future Research ◽  
Building Industry ◽  
Scientometric Analysis ◽  
The Past ◽  
Evolution Pattern ◽  
The Status

Since the 21st century, the concept of green building has been gradually popularized and implemented in more countries, which has become a popular direction in the area of sustainability in the building industry. Over the past few decades, many scholars and experts have done extensive research on green building. The purpose of this paper is to systematically analyze and visualize the status quo of green building. Therefore, based on Web of Science (WoS), this paper analyzed the existing knowledge system of green building using CiteSpace, identified keywords related to green building and their frequency of occurrence using the function of keyword co-occurrence analysis, recognized five clusters using the function of cluster analysis, and explored the knowledge evolution pattern of green building using citation bursts analysis in order to reveal how research related to green building has evolved over time. On the basis of aforementioned keywords, clusters, and citation bursts analysis, this paper has built a knowledge graph for green building. This paper can help readers to better understand the status quo and development trend of green building and to easier recognize the shortcomings in the development of green building, so as to provide a promising direction for future research.

Dirty Work and Dirtier Work: Differences in Countering Physical, Social, and Moral Stigma

2014 ◽  
Vol 10 (1) ◽  
pp. 81-108 ◽  
Author(s):  
Blake E. Ashforth ◽  
Glen E. Kreiner
Keyword(s):  
Distinct Group ◽  
The Other ◽  
Future Research ◽  
Identity Threat ◽  
Dirty Work ◽  
Exotic Dancers ◽  
Organization Level ◽  
Group A

The literature on dirty work has focused on what physically (e.g., garbage collectors), socially (e.g., addiction counsellors), and morally (e.g., exotic dancers) stigmatized occupations have in common, implying that dirty work is a relatively monolithic construct. In this article, we focus on thedifferencesbetween these three forms of dirty work and how occupational members collectively attempt to counter the particular stigma associated with each. We argue that the largest differences are between moral dirty work and the other two forms; if physical and social dirty work tend to be seen as more necessary than evil, then moral dirty work tends to be seen as more evil than necessary. Moral dirty work typically constitutes a graver identity threat to occupational members, fostering greater entitativity (a sense of being a distinct group), a greater reliance on members as social buffers, and a greater use of condemning condemners and organization-level defensive tactics. We develop a series of propositions to formalize our arguments and suggest how this more nuanced approach to studying dirty work can stimulate and inform future research.

A scientometric analysis of BIM studies in facilities management

2019 ◽  
Vol 37 (2) ◽  
pp. 122-139 ◽  
Author(s):  
Mustafa Hilal ◽  
Tayyab Maqsood ◽  
Amir Abdekhodaee
Keyword(s):  
Mapping Method ◽  
Facility Management ◽  
Future Research ◽  
Scientometric Analysis ◽  
Facilities Management ◽  
Science Mapping ◽  
Content Type ◽  
Visual Maps ◽  
Building Information ◽  
Mapping Techniques

Purpose The purpose of this paper is to statistically classify and categorize Building Information Modelling (BIM)-Facility Management (FM) publications in order to extract useful information related to the adoption and use of BIM in FM. Design/methodology/approach This study employs a quantitative approach using science mapping techniques to examine BIM-FM publications using Web of Science (WOS) database for the period between 2000 and April 2018. Findings The findings guide the researchers who are interested in the BIM-FM model by providing visual maps analysis of that area in a simple, easy and readable way. In addition, they help the researchers to understand which authors and journals to consider when dealing with BIM-FM topics. Finally, knowledge gaps in this domain can be identified easily using the findings of the Scientometric analysis. Research limitations/implications First, the results of the analysis depend on the database that has been extracted from WOS, and therefore it carries any of WOS’s limitations in terms of how much it covers the published studies. Another limitation is that the study is based on exploration of “what” questions, rather than “how” and “why”. These limitations represent the hot topics to be addressed in future research. Originality/value This research is the first to conduct the Scientometric Analysis of BIM-FM topics, in which 68 top-ranked publications were systematically examined using a Science Mapping method through VOSviewer software.

scholarly journals Corporate Social Responsibility Performance & ETF Historical Market Volatility

2017 ◽  
Vol 9 (10) ◽  
pp. 30
Author(s):  
Vasiliki A. Basdekidou ◽  
Artemis A. Styliadou
Keyword(s):  
Corporate Governance ◽  
Community Development ◽  
Fair Trade ◽  
Green Building ◽  
Market Volatility ◽  
The Other ◽  
Future Research ◽  
Financial Instruments ◽  
Corporate Social ◽  
Number Of Firms

In investment and trading, different CSR moral ethical firms, categorized in a number of groups, may be suitable for different financial instruments (i.e. USA sector ETFs) and different market volatility situations. For the purpose of this article we first (i) analyze the trading return performance of four CSR categories (in particular: activism, community development, corporate governance, and environment); and then (ii) examine and comment the correlation between the market performance of a number of firms belonging in these four CSR categories and historical ETF market volatility. Finally, we (iii) suggest CSR firms as trading tools according to dominant market volatility. Other CSR categories (like: fair trade & supply chain, green building, philanthropy & corporate contributions, etc.) would be examined in future research by following the introduced by this paper approach. Paper concludes that, in relatively less volatile markets the Environment CSR ethical firms display better results. On the other hand, in strong market volatile situations it is better to trade Community Development CSR and Corporate Governance CSR ethical firms. Finally, the Activism CSR ethical firms are uncorrelated with the market volatility, as well as their performance is poor in all market cases.

scholarly journals Sentiment Analysis of Suicide Notes: A Shared Task

2012 ◽  
Vol 5s1 ◽  
pp. BII.S9042 ◽  
Author(s):  
John P. Pestian ◽  
Pawel Matykiewicz ◽  
Michelle Linn-Gust ◽  
Brett South ◽  
Ozlem Uzuner ◽  
...  
Keyword(s):  
Preliminary Analysis ◽  
The Other ◽  
Future Research ◽  
Large Set ◽  
Biomedical Domain ◽  
Shared Task ◽  
Clinical Text ◽  
Evaluation Measures ◽  
Suicide Notes ◽  
Data Production

This paper reports on a shared task involving the assignment of emotions to suicide notes. Two features distinguished this task from previous shared tasks in the biomedical domain. One is that it resulted in the corpus of fully anonymized clinical text and annotated suicide notes. This resource is permanently available and will (we hope) facilitate future research. The other key feature of the task is that it required categorization with respect to a large set of labels. The number of participants was larger than in any previous biomedical challenge task. We describe the data production process and the evaluation measures, and give a preliminary analysis of the results. Many systems performed at levels approaching the inter-coder agreement, suggesting that human-like performance on this task is within the reach of currently available technologies.

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