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The research on educational gamification spans many topics of interest. As the total volume of research in this area has greatly increased in the last 10 years, it is interesting to see how the interest in the respective topics has changed over the same period. In this paper, we answer this question by means of keyword analysis performed on 7572 unique keywords extracted from 2203 papers. The obtained results reveal (1) the high popularity of keywords that are non-obviously relevant to gamification, (2) vast disproportions in the volume of research dedicated to different aspects of the same research sub-area, and (3) differing patterns of popularity among the most frequent keywords, as well as (4) keywords introduced and abandoned in recent years. The presented findings bear a number of implications for the future of research on educational gamification. [ABSTRACT FROM AUTHOR]

Academic failure and school dropout, or early school leaving, are two of the situations that most concern countries and educational institutions worldwide, because of their prevalence and also their economic and social implications. Despite this prominent role that academic failure and school dropout have in societies, there seems to be no consensus on the literature on their conceptualization, definition, and relationship. Moreover, it is frequent to observe how both concepts are confused or overlap in the scientific literature and how many authors avoid defining these constructs, using them indistinctly. Therefore, this work analyses whether educational research considers them as two different concepts or if they are used indistinctly. For this purpose, 2,051 keywords from 450 articles were subjected to a systematic review and classified into the Education Resources Information Center (ERIC) thesaurus´ descriptors. The results reveal statistically significant differences in the descriptors according to the type of paper to which they correspond (academic failure or dropout). Thus, academic failure is associated with sociocultural, personal, and academic factors, while dropout is linked to employment and educational trajectories. These differences evidence that, although academic failure and school dropout refer to closely related educational problems, there are remarkable differences between them and between the treatment given to each of them in the scientific literature. Therefore, they should be considered as two different concepts. For all this, keyword analysis has proved to be a relevant element for the study of the structure of knowledge, allowing to clearly establish the differences between the two closely related concepts. [ABSTRACT FROM AUTHOR]

Antibiotic-resistant bacteria (ARB) are a serious threat to the health of people and the ecological environment. With this problem becoming more and more serious, more countries made research on the ARB, and the research number has been sharply increased particularly over the past decade. Therefore, it is quite necessary to globally retrace relevant researches on the ARB published from 2010 to 2020. This will help researchers to understand the current research situation, research trends and research hotspots in this field. This paper uses bibliometrics to examine publications in the field of ARB from 2010 to 2020 that were retrieved from the Web of Science (WOS). Our study performed a statistical analysis of the countries, institutions, journals, authors, research areas, author keywords, Essential Science Indicators (ESI) highly cited papers, and ESI hotspots papers to provide an overview of the ARB field as well as research trends, research hotspots, and future research directions in the field. The results showed that the number of related studies is increasing year by year; the USA is most published in the field of ARB; China is the most active in this field in the recent years; the Chinese Acad Sci published the most articles; Sci. Total Environ. published the greatest number of articles; CM Manaia has the most contributions; Environmental Sciences and Ecology is the most popular research area; and “antibiotic resistance,” “antibiotics,” and “antibiotic resistance genes” were the most frequently occurring author keywords. A citation analysis showed that aquatic environment-related antibiotic resistance is a key research area in this field, while antimicrobial nanomaterial-related research is a recent popular topic.

By reviewing scientific literature, researchers may obtain a comprehensive understanding of field developments, keeping abreast of the current research status and hotspot shifts. The evolution pattern of keywords is supposed to be an efficient indicator in revealing the shifting and sustainability configuration of scientific concepts, ideas, and research hotspots. Here we take an extensive investigation of the evolution of keywords among all publications in PNAS Social Sciences from 1990 to 2021. Statistical tests show the keyword mention time series always accompanied by the emergence of a log-normal distribution. Additionally, we introduce a novel schema of four patterns (TELS), which are Transient impact type, Explosive impact type, Large impact type, and Small impact type, respectively, to illustrate the evolution of keywords. The TELS schema can be used to capture the whole life circle feature of any proposed keyword, from a pool of candidates. By dividing the entire time into four periods, we also introduce the concept of elite keywords to reveal the temporal feature of social sciences focus. An explicit transition from anthropology research to neuroscience and social problems research can be observed from the evolution diagram. We argue that the proposed method is of general sense and might be applicable to other fields of science.

This paper presents research trends, leading publishers, influential articles, and shifting concerns in the field of Revenue Management for over forty years based on bibliometric analysis. Bibliometric data was retrieved from Web of Science core collection with a well-defined strategy. The data was processed using Network Analysis Interface for Literature Studies Project scripts. Subject-wise and year-wise research trends were presented. The shifting concerns in RM in terms of topic, method, and domain were highlighted using keyword analysis. In general, RM showed an increasing number of published papers with exponential manner every year. The research core in RM covered the three major decisions in RM including pricing, quantity control, and structural decision. It was highlighted that RM’s concern has shifted from single-firm decision to be more consumer- and competition-centric. The data showed that the needs of empirical study and more advanced quantitative methods for complex and real-time problems were urged. In addition, the adoption of RM was extended for industries with semi-flexible capacity. The top influential publishers were Decision Sciences, Operations Research, Management Science, and Management Science Manufacturing & Service Operations Management.

In this paper, the tool of bibliometric analysis is applied to the field of activated sludge modelling and its suitability as a first step of a literature analysis is assessed. The analysis is applied to the total dataset considered as well as a time-based classification. It can be shown that this tool is very well suited to filtering the relevant authors and publications, thus enabling a subsequent visual review. The methodology presented can also be applied to sub-disciplines or other subject areas. However, the sole use of the multiple statistical and visual tools is critically questioned. Thus, misinterpretations and apparent findings can result from structural problems in the data or parameters used. Not all of the metrics used are suitable for finding relevant publications, but rather for ranking the criteria studied. However, the latter represents the most widespread application of bibliometrics. From the analysis of the keywords, it could be deduced that there has been a temporal shift from fundamental model aspects to detailed questions such as the integration of sorption and adsorption processes or anaerobic digestion. The modelling of biological phosphorus removal has also surprisingly lost a great amount of importance in the scientific literature. HIGHLIGHTS First application of a bibliometric analysis in the field of activated sludge modelling with specific guidance for implementation.; Demonstration that the tool can be used to analyse very clear trends in research based on time-dependent measures.; Evidence of the importance of using such a tool in analysing the diversity of information available today in combination with professional expertise by users.;

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The article outlines the options for a pedagogically motivated keyword analysis in order to discover differences between the academic writing of Czech and Austrian students of German philology (or related fields). First, the paper presents a brief overview of the presently available metrics employed in keyword analyses, outlining some modifications that can be applied to make the results more relevant and easily interpretable. In the practical part, I explore which lexical items are frequently used by the L1 writers but at the same time are underused in the L2 subcorpus. The product of the study is a word list, which can be utilised by academic writing instructors or students themselves to provide them with an idea of what needs to be taught/learnt. [ABSTRACT FROM AUTHOR]

A huge amount of data is collected by search engines. According to estimates, the Google search engine, which is dominant on the market, receives billions of search requests daily. Of particular note is that a large part of the collected data is available through the Google Trends service. As a consequence, various types of data can be used by enterprises for their development but they often do not take advantage of this opportunity. Therefore, the purpose of this article is to prove the suitability of the big data concept for creating and implementing product innovations, using the example of Google Trends. Discovering human needs and searching for answers to them is not only the domain of entrepreneurs, therefore this study may have a fairly broad practical applications. By adopting general assumptions, i.e. ones that do not refer to specific products or industries, the author has shown that the presented path may be recreated by both entrepreneurs and creators of political programs, as well as leaders of non-governmental organizations who need to implement innovations. The results revealed the selection of specific ways of entering queries in Google Trends and certain periods of analysis which are the most useful for creating innovations. Descriptive statistics (such as median) clearly show that the results typed in Google Trends are better when taken from a user perspective and can be used to create innovations. Despite substantial differences, the results do not allow for the conclusion that these differences were statistically significant. Thus, preliminary data supports the hypothesis, but more research is needed. [ABSTRACT FROM AUTHOR]

Contrary to the optimistic expectations three decades ago, global military expenditure is increasing rather rapidly, fueled by the increasing intensity of international tensions. As a consequence of this, the military-caused soil pollution gains in importance. On the basis of a bibliometric analysis of 3500 articles, it is obvious that the level of interest in this topic has been rather fluctuating in the last decades, but in the last years, more than two hundred and fifty new publications have been appearing annually. The majority of publications are authored by US, Chinese, and Western European authors. Five main research areas could be identified by the cluster analysis of the following keywords: Heavy metal pollution, water resource pollution, consequences of soil pollution in the food chain, pollution by organic components and soil remediation, and analytic method development. The most central problem of research is heavy metal contamination. The basic topics of research are risk management, water contamination, and the depleted uranium problem. There is a further need to study the possibilities of decreasing of level of chemical pollutants, especially heavy metals. [ABSTRACT FROM AUTHOR]

Research on weapon systems has been conducted, and defense drones have been developed. However, few analyses that identify the needs of the general public have been conducted. The purpose of this study is to analyze the issues of interest in social networks regarding defense drones and extract keywords for activation. In this study, big data analysis tools such as Textom, Ucinet6, and NetDraw were used. The results of the keyword frequency analysis, centrality analysis, and CONCOR analysis showed that public information regarding social networks expressed keywords in defense drones, such as Defense Daily, News, Enterprise, Defense Science Research Institute, University, Hydrogen Battery, Army, Air Force, Urban Transportation, Fire, Regional, Enterprise, and Research. It is necessary to revitalize media publicity in developing cooperative technologies by companies, universities, the National Defense Research Institute, urban transportation, and firefighting, using army and air force drones, and developing future hydrogen batteries. In addition, issues of interest were observed for contents, such as applications in the United States, Israel, North Korea, Iran, and Afghanistan, and fostering university education. There is a need to present a case for the actual military use of defense drones and train the department of defense drones at universities.

Genre definitions by Swales (1990) and Miller (1984) include the communicative purpose of a text as an indicative feature of its genre. Genre studies have also identified how expert members of discourse communities possess professional expertise in genre styles. This article shows that beyond discourse community expert members, ordinary audiences also have conceptions of genre and use those conceptions to evaluate texts. Through a corpus-assisted discourse analysis of listener reviews of the true crime-comedy podcast My Favorite Murder, the analysis shows that negative reviews view the true crime-comedy categorisation as two separate genres, evaluating the podcast based on expectations of true crime and expectations of comedy. Positive reviewers accept the true crime-comedy genre as a new, mixed genre and evaluate the podcast from an in-group perspective, identifying themselves as members of the My Favorite Murder discourse community. Through this analysis, I show that audiences implement some form of genre analysis in text evaluations and that membership of the discourse community influences how they apply genre expectations to evaluations of texts. [ABSTRACT FROM AUTHOR]

There is still much to learn about the ways in which human and machine translation differ with regard to the contexts that regulate the production and interpretation of discourse. The present study explores whether a corpus-driven lexical analysis of human and machine translation can unveil discourse features that set the two apart. A balanced corpus of source texts aligned with authentic, professional translations and neural machine translations was compiled for the study. Lexical discrepancies in the two translation corpora were then extracted via a corpus-driven keyword analysis, and examined qualitatively through parallel concordances of source texts aligned with human and machine translation. The study shows that keyword analysis not only reiterates known problems of discourse in machine translation such as lexical inconsistency and pronoun resolution, but can also provide valuable insights regarding contextual aspects of translated discourse deserving further research. [ABSTRACT FROM AUTHOR]

Background: Detecting the main actors and important topics of Iranian cancer research is essential for Iranian policymakers, clinicians, and researchers. This study was conducted to demonstrate the trends and tops in Iranian cancer research from 1960 to 2018. Methods: A total of 22,370 Iranian cancer articles in Web of Science (WoS), PubMed, and Scopus, from 1960 through 2018, were extracted and preprocessed based on data mining techniques and analyzed using the collaboration network analysis, keywords analysis, and bibliometrics methods. Results: The results reveal that, Tehran University of Medical Sciences (11.46%) among organizations, Asian Pacific Journal of Cancer Prevention (5%) among journals, Malekzadeh R (1.09%) among authors, and Breast cancer (10.37%) among topics ranked the first. The trend of Iranian cancer research represents three periods: 1) germinating period, from 1970 to 2000, 2) developing period, from 2002 to 2014, and 3) flourishing period, from 2014 to 2018. It is expected that this trend will continue. The results indicate an average 12.8% increase in the logarithm of the count of articles published by Iranian cancer researchers each year. The findings are contextualized with Price’s publications trends principal for determining global and Iranian cancer research publication trends. Conclusion: The number of research papers published by Iranian researchers on cancer is increasing. In order to maintain the publication growth in this field, greater participation by other Iranian institutions is suggested. Although the quantity and quality of papers are increasing in some topics, certain topics and types of cancers should be still further studied and the Iranian policymakers should be encouraged to invest more in these topics. [ABSTRACT FROM AUTHOR]

The Open Geospatial Consortium (OGC) is an international non-profit standards organization. Established in 1994, OGC aims to make geospatial information and services FAIR-Findable, Accessible, Interoperable, and Reusable. OGC specifications have greatly facilitated interoperability among software, hardware, data, and users in the GIS field. This study collected publications related to OGC specifications from the Web of Science (WoS database) between 1994 to 2020 and conducted a literature analysis using Derwent Data Analyzer and VosViewer, finding that OGC specifications have been widely applied in academic fields. The most productive organizations were Wuhan University and George Mason University; the most common keywords were interoperability, data, and web service. Since 2018, the emerging keywords that have attracted much attention from researchers were 3D city models, 3D modeling, and smart cities. To make geospatial data FAIR, the OGC specifications SWE and WMS served more for "Findable", SWE contributed more to "Accessible", WPS and WCS served more for "Interoperable", and WPS, XML schemas, WFS, and WMS served more for "Reusable". The OGC specification also serves data and web services for large-scale infrastructure such as the Digital Earth Platform of the Chinese Academy of Sciences. [ABSTRACT FROM AUTHOR]

Advertisements demonstrate patterns of communication that are imagined to be acceptable to the communities at which they are aimed, serving as cultural artefacts that provide insights into shared cultural interpretations and social interactions. Drawing on techniques from corpus linguistics, text linguistics and the Appraisal framework, we conducted an analysis of salient keywords in a collection of Thai and Japanese tv commercials (tvcs) for insurance products in order to identify statistically significant keywords and examine emotional engagement. We reveal how specific keywords and communicative strategies used in the persuasive discourse of the insurance products reflect Thai and Japanese socio-cultural preferences and values. We found that while Thai tvcs demonstrate a higher audience engagement through the use of metadiscourse markers such as engagement markers and emphatics under the theme of moral and family values, Japanese tvcs highlight information-dense content-words, including the extensive use of statistics involving themes of security, health and value propositions. [ABSTRACT FROM AUTHOR]

In recent years, bibliometric analysis as a field of study has captured researchers' interest worldwide. Bibliometric analysis enables one to have data about a particular field of research in one place. In this paper, the authors have attempted to capture insights on the study of bibliometric analysis of corporate governance in BRICS economies. For all companies, and most prominently the publicly traded companies, reliance to the ethos of good corporate governance helps enhance the value of the companies. Corporate governance is an umbrella term indicating all possible areas of best practice to elevate the performance of the companies. BRICS economies have their own set of similarities as well as differences. Bibliometric analysis of corporate governance research is elaborately studied in the context of European and other developed economies. As this kind of study has not been done with reference to the BRICS economies, we had the motivation to conduct this study. From the Scopus database, meta data has been collected for this study. In this study, we reviewed 3,596 research publications during the last three decades, between 1991 and 2020. The increasing trend of publications is observed in corporate governance in BRICS countries using the longitudinal data. Researchers from China rule the chart on the quantum of research done in the field of corporate governance among the BRICS economies. Meta data for ten years is analysed using Biblioshiny and Vosviewer. Using a thematic map, the study of 3,596 documents were divided into four time zones, i.e., 1991-2011 (976 documents), 2011-2014 (612 documents), 2014-2017 (792 documents), and 2017-2020 (1,296 documents). The key themes which emerged were governance and ownership structure (1991 to 2011); stakeholders, corporate social responsibility, and internationalisation (2011-2014); privatisation and investor protection (2014-2017); and audit committee, independent directors, and corporate governance (2017-2020).. [ABSTRACT FROM AUTHOR]

Background: Given the increasing number and survival rates of reproductive-age patients with chronic myeloid leukemia (CML), several studies aimed to elucidate optimum disease management in pregnancy. This study aimed to use bibliometric analysis to assess focus and reported insights, as well as future trends, in CML and pregnancy research. Methods: We extracted all studies related to CML and pregnancy from the Web of Science database from 2001 to 2020. VOS Viewer, CiteSpace, Python, and R-bibliometrix were used for bibliometric analysis, revealing the leading research countries, institutions, and authors, as well as distribution of keywords (frequency greater than five). Results: A total of 196 records, published in 137 journals by 1,105 authors from 421 research institutes in 50 countries, were identified for analysis. The United States was the leader in the number of publications. Imperial College London and National Research Center for Hematology were the most influential institutions. In addition, Apperley J, Cortes J, Abruzzese E and Kantarjian H were the leading authors in the field. Keyword analysis identified four research hotspot clusters. Conclusions: This study systematically analyzed the progress in CML and pregnancy research in the last 20 years. The present findings suggest that the management of planned and unplanned pregnancies in patients with CML will remain a research focus, as further evidence is required for the development of treatment guidelines. [ABSTRACT FROM AUTHOR]

Plant allelopathy is a biological phenomenon in which plants adapt to defend against the pests (weeds, insects, nematodes and pathogens) adverse environment. It is one of the hotspots in Ecology and Agronomy. In this paper, we have retrieved from the Web of Science (WoS) SCI-E database the allelopathy-related studies (1960-2019). The Annual Number of Publications, Authors, Countries, Institutions, Journals and Keywords were analyzed by the bibliometric method to determine the research trends and hotspot changes in this field over the past 6 decades. From 1960-2019, the WoS database included 4,114 studies in the field of plant allelopathy. During this period of 60 years, the number of publications has gone through three stages: (i). Initial Stage (1960-1990), (ii). Growing Stage (1991-2009) and (iii). Stable Stage (2010-2019). The studies were conducted by 9,956 authors at 2,166 institutions across 100 countries. The United States, China, and Japan have the highest number of publications. The top three institutions with the highest number of publications are the Chinese Academy of Sciences, Kagawa University and USDA, USA. The top three authors are H. Kato-Noguchi, F.A. Macias, and C.H. Kong. The major Journals in this field are: (i). Allelopathy Journal, (ii). Journal of Chemical Ecology and (iii). Plant and Soil. The results of keyword clustering showed that the main research directions in this field are: (i). Metabonomics undergoing allelopathy, (ii). Functions of allelopathy substances, (iii). Molecular biology, (iv). Allelopathy of aquatic plants, (v). Alien plants invasion and (vi). Application of plant allelopathy in agroforestry production. Plant allelopathy is a research field that aims to maintain stable development. Future studies should focus on strengthening the cooperation among international scholars in plant allelopathy research and improving the output in frontier and hotspot areas. [ABSTRACT FROM AUTHOR]

This study explores the influence of a government’s ideology on linguistic representation in a news agency that characterizes itself as independent. It focuses on the coverage of the Syrian civil war as reported by the Iranian news agency Fars, addressing the discursive constructions of anti-government powers in relevant online reports released between 2013 and 2015. Since the Islamic Republic of Iran was a major regional ally of the Syrian government, we questioned the extent to which ideological independence could be expected during a politically critical time frame. Taking a corpus-based linguistic approach, the study explores the semantic macrostructures representing the opposition as well as the lexical clusters and keywords characterizing the news discourse. The findings indicate that Fars’ representation of the Syrian Revolution was, to some extent, biased, despite its claimed independence of the government’s political stance. It excluded the Sunni social actors, suppressed the Islamic faction identity of the rebels and depicted the uprising as a war against foreign-backed militants. The rebels were stereotyped in terms of terrorism and non-Syrians. In addition, the analysis reveals Fars’ tendency to emphasize the power of the government, depicting it as the defender of the Arab land and foregrounding the discourse of international conspiracy against Syria. The results of this work project the dimension of media bias caused by the underpinning political perspective of media institutions.

BackgroundGiven the increasing number and survival rates of reproductive-age patients with chronic myeloid leukemia (CML), several studies aimed to elucidate optimum disease management in pregnancy. This study aimed to use bibliometric analysis to assess focus and reported insights, as well as future trends, in CML and pregnancy research.MethodsWe extracted all studies related to CML and pregnancy from the Web of Science database from 2001 to 2020. VOS Viewer, CiteSpace, Python, and R-bibliometrix were used for bibliometric analysis, revealing the leading research countries, institutions, and authors, as well as distribution of keywords (frequency greater than five).ResultsA total of 196 records, published in 137 journals by 1,105 authors from 421 research institutes in 50 countries, were identified for analysis. The United States was the leader in the number of publications. Imperial College London and National Research Center for Hematology were the most influential institutions. In addition, Apperley J, Cortes J, Abruzzese E and Kantarjian H were the leading authors in the field. Keyword analysis identified four research hotspot clusters.ConclusionsThis study systematically analyzed the progress in CML and pregnancy research in the last 20 years. The present findings suggest that the management of planned and unplanned pregnancies in patients with CML will remain a research focus, as further evidence is required for the development of treatment guidelines.

Since the scope of social responsibility is not clear both at the institutional level and the academy, it is difficult to determine its limits. In order to clarify this issue, explain the thematic distribution, and structure of the literature social responsibility theses written in Turkey in the last 35 years are analyzed by bibliometric analysis and content analysis. The fact that business literature is at the center of the concept social responsibility explains that 90% of the theses are written in the Institute of Social Sciences, and 40% in the Business Department which is also reflected in the theses titles. The strongest cluster of studies focuses on social responsibility practices in the Turkish private sector regarding brand and corporate image, reputation, ethical values, and financial performance. Most of the stakeholder studies are about consumer buying behavior and employee loyalty relationship. Special attention has been paid to the tourism and banking sectors, other sectors have not been adequately researched. Nongovernmental organizations, volunteering, and international standards have been studied in a limited number. A.B.Carroll, is the dominant author, both as the author of the top three most cited articles, and the first in the ranking with a distinct difference from other authors. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a bibliometric analysis of scientific documents in the field of traumatic brain injury rehabilitation. Methods: Web of Science was used to collect bibliographic data of traumatic brain injury rehabilitation documents from 1983 until the end of 2017. Results: Of a total of 6069 documents retrieved, 78.2% were journal articles. The average annual growth of the documents as of the year 2000 was 9.4%. The most frequent subject categories in this field were Rehabilitation, Neurosciences and Neurology, Sport Sciences, Psychology, and General and Internal Medicine. The most active journal was Brain Injury. More than 50% of the documents were published in 10 journals. The most prolific and impactful institutions were from the USA, Australia and Canada. Traumatic brain injury, rehabilitation, brain injury, stroke and outcome were the most commonly used keywords. Mild traumatic brain injury and concussion were the topics receiving attention in recent years. Conclusion: Traumatic brain injury rehabilitation is a young and constantly growing field. Since the late 1990s, traumatic brain injury rehabilitation documents published yearly comprised about 3–4% of all rehabilitation documents. It was shown that review papers and proceedings have more impact than journal articles, and collaborative papers receive more citations. It was also revealed that knowledge does not become obsolete rapidly in this field. [ABSTRACT FROM AUTHOR]

This article examines Finnish online forum discussions where religion and discourses of 'homosexuality' are connected in various ways. Previous research (e.g. Jantunen 2018a) shows that in Finnish online discussions where sexual minorities are the topic, religion stands out as a significant feature – particularly in discourses on 'homosexuality'. Via corpus-assisted discourse analysis (CADS), the present study adds to previous knowledge on this subject by qualitatively analyzing the occurrences of certain keywords in the Finnish societal context – one in which immigration and the visibility of both Islam and sexual minorities are perceived to have increased. The analysis found four interrelated key discourses in these online discussions: (1) Islamization as an alleged threat to gay people (in the data: 'homosexuals'); (2) the alleged indifference/ignorance of people to Islam's stance against sexual minorities; (3) relativist discourse(s) claiming all fundamentalists to be similar; and (4) othering – including for instance, the verbal stylization of Muslims as being particularly hypersexual. [ABSTRACT FROM AUTHOR]

Transportation systems play a vital role in contributing to the economic growth and social development of urban areas. However, a number of transportation-related issues continue to plague many urban areas. Intelligent transportation systems (ITS) were introduced to solve some of these urban issues by combining advanced technologies and operational management into existing transportation systems; and many researchers and transportation professionals have contributed numerous theoretical and practical solutions toward the evolution of ITS. As transportation agencies continue to invest in existing transportation facilities, an understanding of their current status for ITS needs and the effects of investments made is required for a strategic long-term policy goal for intelligent transportation. This paper presents indicators we found that can be utilized for a consistent ITS development strategy for road appurtenances and operational management to promote intelligent road infrastructure (IRI) in urban cities. We developed these indicators utilizing a text mining technique that generated a total of 23 indicators under the service categories of the International Organization for Standardization (ISO). Using the indicators enables city officials to establish a consistent strategy in assessing the current status of urban roads and monitor the effects of investments made towards a long-term policy goal for ITS. Another contribution of our indicators is their dedicated use for urban road appurtenances and operational management, differentiating them from other ITS-related indicators. Our indicators can be assimilated easily into the need analysis at city-wide ITS planning programs due to their compatibility and can be extended to future research to develop factors to prioritize ITS needs and decision-making for cost-effective investments. • Indicators were developed to apply for road appurtenances and operational management. • City officials can use the indicators to establish a consistent ITS development strategy. • The indicators were developed to be compatible with city-wide ITS planning programs. • The indicators can potentially be extended to prioritize the ITS performance of urban road infrastructure. [ABSTRACT FROM AUTHOR]

The paper uses keyword analysis as the empirical basis for the characterization of Shakespeare’s character Iago from Othello, the Moor of Venice. The aim of the paper is to determine how Iago’s manner of speech reflects his deceitful and manipulative nature and how it differs from the speech-styles of non-deceitful prominent characters: Othello, Cassio, Roderigo, Desdemona and Emilia. Keywords for the chosen characters are based on the corpora of character speech and the Sketch Engine tool is used to process the data. The results are then interpreted and discussed on the basis of six interconnected points of discussion: focus, adjectives, use of the expression Moor, references to the handkerchief, poisoning-the-ears technique, and pronouns, all of which confirm that Iago’s manipulative nature is indeed evident in his speech and that there is a clear difference between his speech-style and the speech-styles of other, non-deceitful, prominent characters.

This paper aims to conduct a quantitative evaluation on the achievement, research productivity, and research hotspots of “Library, Information and Archives management” Science schools or departments in China. In this paper, the “LIS” in China is firstly defined. Before evaluation, data are collected from CSSCI (Chinese Social Science Citation Index)-indexed papers and SSCI (Social Science Citation Index)-indexed papers, as well as projects granted by the two authoritative national foundations in China, SSFC (National Social Science Foundation of China) and NSFC (National Natural Science Foundation of China). Then, a bibliometric-based method and a keyword-based method are employed to analyze the collected data from different perspectives, including annual distribution, author productivity, institute productivity and influence. Through the analysis, several conclusions are made: a) collaborative groups exist, though no particular collaboration preference is exhibited. b) Interdisciplinary research promotes the emergence of new disciplines. c) There are four top institutes with outstanding productivity and six hot research topics in the “LIS” study in China. Also, in a five-year period, “LIS” scholars have paid much attention on network technology and its application in this field. Research addressing the view of “information” is much more popular than the ubiquitous conception of “library”. d) There still exist some issues in China's LIS research, for example, the unbalanced development of educational institutes, the excessive preference of theoretical research over technical research, etc. [ABSTRACT FROM AUTHOR]

Almost a century after Jacob Levy Moreno pioneered the group practice of psychodrama, research in this area has flourished to include different sub-fields of study and psychodramatic intervention for various psychological conditions. By making use of scientometric analysis, particularly document citation analysis and keyword analysis, this study maps out dominant research domains in psychodrama since its inception. From these findings, projections of future research trends and an evaluation of psychodrama research are discussed. Generally, there has been an increased adoption of technology to facilitate psychodrama practice, along with an increasing integration of psychodramatic principles with other psychotherapies. To improve research in this area, this paper recommends greater transparency in the reporting of materials, processes and data used in publications. Finally, we encourage embracing new technological methods such as neuroimaging to provide greater insight into mechanisms of change in psychodrama. The field of psychodrama remains full of potential and innovations to be developed. [ABSTRACT FROM AUTHOR]

This study assesses the nature of Canada’s rapid research response through term and keyword bibliometric analysis. The following asks: What are the major areas of COVID-19 rapid research output conducted in Canada during the first five and half months of 2020, and how can the results of this analysis inform future accelerated research efforts toward an effective response to infectious disease emergencies? The results suggest that infection prevention, epidemiology, therapeutics, and public health strategies were among the topproducing research areas in Canada during the onset of the pandemic. Moreover, the analysis reflects gaps in the literature addressing diagnostics and vaccine development. [ABSTRACT FROM AUTHOR]

• We compare the performances of various typical semantic representation methods for keywords across four domains. • Keyword clustering is utilized as the assessment task, and we propose a method for constructing the "gold evaluation standard" specific to each domain. • The co-word matrix exhibits subpar performance, while the co-word network and word embedding methods demonstrate strong performance. The network embedding methods yield varied results. • We exhibit distinct attributes and applications of each method to meet the need of different application scenarios. Semantic representation methods play a crucial role in text mining tasks. Although numerous approaches have been proposed and compared in text mining research, the comparison of semantic representation methods specifically for publication keywords in bibliometric studies has received limited attention. This lack of practical evidence makes it challenging for researchers to select suitable methods to obtain keyword vectors for downstream bibliometric tasks, potentially hindering the achievement of optimal results. To address this gap, this study conducts an experimental comparison of various typical semantic representation methods for keywords, aiming to provide quantitative evidence for bibliometric studies. The experiment focuses on keyword clustering as the fundamental task and evaluates 22 variations of five typical methods across four scientific domains. The methods compared are co-word matrix, co-word network, word embedding, network embedding, and "semantic + structure" integration. The comparison is based on fitting the clustering results of these methods with the "evaluation standard" specific to each domain. The empirical findings demonstrate that the co-word matrix exhibits subpar performance, whereas the co-word network and word embedding techniques display satisfactory performance. Among the five network embedding algorithms, LINE and Node2Vec outperform DeepWalk, Struc2Vec, and SDNE. Remarkably, both the "pre-training and fine-tuning" model and the "semantic + structure" model yield unsatisfactory results in terms of performance. Nevertheless, even with variations in the performance of these methods, no singular approach stands out as universally superior. When selecting methods in practical applications, comprehensive consideration of factors such as corpus size and semantic cohesion of domain keywords is crucial. This study advances our understanding of semantic representation methods for keyword analysis and contributes to the advancement of bibliometric analysis by providing valuable recommendations for researchers in selecting appropriate methods. [ABSTRACT FROM AUTHOR]

The research on educational gamification spans many topics of interest. As the total volume of research in this area has greatly increased in the last 10 years, it is interesting to see how the interest in the respective topics has changed over the same period. In this paper, we answer this question by means of keyword analysis performed on 7572 unique keywords extracted from 2203 papers. The obtained results reveal (1) the high popularity of keywords that are non-obviously relevant to gamification, (2) vast disproportions in the volume of research dedicated to different aspects of the same research sub-area, and (3) differing patterns of popularity among the most frequent keywords, as well as (4) keywords introduced and abandoned in recent years. The presented findings bear a number of implications for the future of research on educational gamification.

Keyword analysis is a way to gain insight into market behaviour. It is a detailed analysis of words and phrases that are relevant to the selected area. Keyword analysis should be the first step in any search engine optimization, as it reveals what keywords users enter into search engines when searching the Internet. The keyword categorization process takes up almost half of the total analysis time, as it is not automated. There is currently no known tool in the online advertising market that facilitates keyword categorization. The main goal of this paper is to streamline the process of keyword analysis using selected statistical methods of machine learning applied in the categorization of a specific example. [ABSTRACT FROM AUTHOR]

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This study has a two-fold structure, in its first part exploring various models of experimental literature, proposed by researchers such as Gerald Prince and Warren Motte, as well as theoretical attempts to define and analyze experimental literature in Romania. The second part focuses on the quantitative analysis of keywords related to “the experimental” found in literary histories of Romanian literature authored by E. Lovinescu, G. Călinescu, Nicolae Manolescu, and Mihai Iovănel, as well as The General Dictionary of Romanian Literature and The Chronological Dictionary of the Romanian Novel. By simply searching several pointedly chosen terms in the corpus, a cartography of what is considered to be experimental emerges clearly, alongside its relation to the canon, to the dynamics of literary genres, and to the temporal evolution of Romanian literature. [ABSTRACT FROM AUTHOR]

This paper aims to analyze lexical properties of keyword lists extracted from NLT Old Testament Corpus(NOTC), NLT New Testament Corpus(NNTC), and The NLT Bible Corpus(NBC) and identify that text dispersion keyness is more effective than corpus frequency keyness. For this purpose, NOTC including around 570,000 running words and NNTC about 200,000 were compiled after downloading the files from NLT website of Bible Hub. Scott’s (2020) WordSmith 8.0 was utilized to extract keyword lists through comparing a target corpus and a reference corpus. The result demonstrated that text dispersion keyness showed lexical properties of keyword lists better than corpus frequency keyness and that the former was a superior measure for generating optimal keyword lists to fully meet content-generalizability and content distinctiveness. [ABSTRACT FROM AUTHOR]