Topic Maps Research Articles

A topic map based learning management system to facilitate meaningful grammar learning: the case of Japanese grammar learning

This study investigates the effect of studying with topic maps provided by a self-developed language learning support system on (a) learning perception, (b) learning achievement and (c) variation in learning attitude and motivation, from the perspective of prior learning attitude, motivation and learning style. An analysis was conducted on the learning data of 90 participants for examining pre-test and post-test scores, learning perception, learning style indicators, attitude and motivation rankings before and after the study of target Japanese grammar content with the support of the system. The findings suggest that learners with high attitude/motivation perceived greater development of the habit of “learning from the comparison of related knowledge” and felt more satisfied with the learning situation in the system environment. Furthermore, the learners' attitude towards Japanese grammar learning and their motivation toward Japanese language learning were significantly stronger after the learning activity. It is also observed that (a) learner attitude towards Japanese grammar after studying with the system only had a positive correlation to prior attitudes; and (b) learner motivation towards Japanese language after studying with the system correlated highly with prior motivation and perception of development of the habit of “learning from the comparison of related knowledge.” Finally, from a learning style perspective, the analysis result suggests that “Global learners” expressed a stronger feeling about the usefulness of the comparison function of the system and their increment in motivation after using the system was higher than for “Sequential learners.” Moreover, between learning style indicators in the Sequential/Global dimension and level of learner expertise in the reported mental load scale, a significant interaction effect was found.

Pemetaan Tren: Analisis Bibliometrik dari Audit Report Lag yang Terindex Google Schoolar

Financial reports are an important thing that is really needed by a company. The audit assessment has an impact on the financial reports that will be published. The study of audit delays is experiencing rapid growth. This has attracted the interest of many researchers to continue developing it, including analyzing internal and external company factors that influence audit delays. However, until now, publications related to this topic have not been well organized. This research aims to map research publications related to audit delays in a database context, with the keyword "audit delays" with the VOSviewer Bibliometric research study. The analytical method used is a quantitative method. Data sources were taken from journals indexed by Google Scholar, Sinta, and Emerald, then analyzed with the help of Publish or Perish and Mendeley Desktop software to screen the data. The results of this research show that in the Vosviewer Bibliometric study there are 3 Clusters and 24 main topics related to Audit Report Lag. This research provides an overview of relevant topic mapping for further research.

Creating a Topic Map for representing Network Security Competencies

Competencies represent the knowledge, skills and attitudes required for job roles. Organisations need to understand and grow competencies within their workforce in order to be more competitive and to maximise new market opportunities. The assessment of competencies can be conceptualised from two perspectives. The first is ‘Competency Frameworks’, which describe competencies from a high-level overview. The second perspective is ‘Competency-Based Learning’, which focuses on addressing competencies from a more detailed, task-oriented perspective. This research presents a tool that can map these two perspectives together. This mapping provides a more holistic approach to describing competencies, which is particularly important to network security occupational job roles. In this research, the Design Science paradigm was used as the methodology for creating and evaluating a topic map.

Charting the evolutionary conceptual pathway of analytic network process research: A main path analysis

AbstractThis study delves into the flow and structure of knowledge prevalent in Analytic Network Process (ANP) literature. It traces the evolutionary pathway of ANP research, spotlighting seminal works and unfolding the development of topics over time. Analysing 4583 ANP literature records from 1986 to 2022, this research utilizes two pivotal data sources: Web of Science (WoS) and Dimensions. This main path analysis (MPA) approach is coupled with techniques such as citation analysis, social network analysis, and centrality measures to identify most influential papers, as well as using a search path algorithm (SPC) to provide higher weights to papers that serve as bridges connecting different research paths rather than simply counting all citations equally. Key works emerged as focal points in both datasets, including notable contributions from Lee, Kheybari and Büyüközkan, with the Dimensions dataset uniquely highlighting Saaty as the initial conceptual knowledge source of the ANP. The centrality measures unearthed persistent bridge roles undertaken by key contributors such as Saaty and Sarkis over different time periods. Furthermore, a detailed topic analysis discerned eight distinctive thematic clusters among the two data sources: analytical network process, network process, fuzzy analytic, evaluation laboratory, supply chain, quality function, hierarchy process, and information systems. These clusters emerged, providing a comprehensive map of ANP topics and their evolution. The study offers a comprehensive framework for scholars to navigate the expansive domain of ANP research. Identifying pivotal works and emergent themes provides direction for future research endeavours. It allows practitioners to gain invaluable insights into the foundational and transformative works in the ANP realm, enhancing their understanding and application of the methodology. This paper proposes of a dual methodological strategy: First, by using traditional academic data sources (WoS) along with a more encompassing Dimensions database; and second, by using a SPC algorithm to weight MPA papers based on their connecting role among different research paths. At the discipline level, this study carves out a novel vantage point in understanding the ANP research landscape. It offers an integrated portrayal of the field's conceptual evolution, identifying specific cluster topics as an indispensable resource for scholars, practitioners, and students.

Sistematik Literatur Review Eksplorasi dan Identifikasi Karakteristik Padi Lokal Sumatra Barat

As much as 75% of people's daily calorie input in Asian countries comes from rice One of the provinces that has great potential as a contributor to national rice production is West Sumatra. Supported by natural resources and good climatic conditions and a large population, which is 4,846,909 people. The purpose of this article is to find out the development and mapping of research topics on Exploration and Identification of Local Rice Characteristics of West Sumatra. The type of research used is literature review using bibliometric analysis. The bibliometric analysis in this study shows a study of the evolutionary process on the research topic with local West Sumatran rice from 2010 to 2023. Vosviewer is an important programming tool for visualizing and analyzing network visualizations in mapping bibliometric analysis. Around 235 articles obtained from the Google Scholar database show that there is a use of the term West Sumatran local rice and can be a topic of future research.

ADVANCMENTS IN TEXT SUMMARIZATION AND EXTRACTIVE QUESTION- ANSWERING : A MACHINE LEARNING APPROACH

In the era of social media platforms, the rapid expansion of data mining in the fields of information retrieval and natural language processing emphasizes the crucial need for automated text summarization. At the current time, pretrained word embedding techniques and sequence to sequence models can be effectively repurposed in the realm of social network summarization to efficiently condense significant information with strong encoding capabilities. However, dealing with the challenge of extended text dependency and efficiently utilizing latent topic mapping presents an increasingly significant obstacle for these computational models. In this document, we propose a topic- focused approach for both extractive and abstractive summarization, integrating Question Answering features by employing BERT and Pegasus pretrained models. A comprehensive analysis of the architectural complexities of the pre-existing models utilized in the creation of our model has been presented. The evaluation of our Text Summarization & Question Answering Model was conducted meticulously on a variety of datasets including Multi news, XSum, and CNN/Daily Mail, with experimental results indicating its achievement of state-of-the-art performance levels based on ROGUE scores. Following this, the verification of our results through human evaluation confirms that the summaries generated by our model are in alignment with the performance standards set by humans across various datasets. Furthermore, we have integrated an Extractive Question Answering task into our model, proposing an architecture leveraging BERT and conducting comparative analyses against alternative language models to gauge its efficacy. Keywords—Natural Language Processing (NLP), Text Summarization, Question & Answering (Q&A), Transformer Models, Pegasus, BERT (Bidirectional Encoder Representations from Transformers), Neural Topic Modeling, Extractive Summarization, Abstractive Summarization, Semantic Representation, Topic Embedding

Determinants of Human Capital Development and Macroeconomic Freedoms: DEA Modelling

The purpose of the study is to identify countries with mechanisms to most effectively ensure that human capital losses do not become an obstacle to strengthening macroeconomic freedoms. The study is based on the hypothesis that a decrease in absence from work due to personal health problems, unemployment, and mortality leads to an increase in the level of six basic macroeconomic freedoms: business, labour, trade, investment, monetary, and financial freedoms. In this case, absence from work due to personal health problems, unemployment, and mortality serve as discouragers/inhibitors of human capital development, the growth of which reduces the chances of an employee obtaining the necessary knowledge and skills to effectively transform this employee’s labour into an economic asset. To generalise the scientific opinion on the studied issue, a bibliometric analysis of the relationship between each of these factors and the totality of all macroeconomic freedoms was carried out using the R Bibliometrix package in RStudio software. The basis of this analysis was formed by the databases of publications indexed by Scopus for 1937–2024, consisting of 1618, 1578, and 1517 literature sources for each factor-destimulator. This analysis allowed us to form clouds of the most used keywords and analyse the dynamics of their use, see how the relevant research areas and the keywords used have evolved, build a topic map of the research interface, etc. The information base of the study is the statistical data of Europa and the Heritage Foundation; the object is 30 European countries; the time horizon is 2021; the main method is the non-parametric method of Data Envelopment Analysis (CCR and BCC models); the software package is the rDEA and Benchmarking package in the R programming language. Frontier graphs were constructed that clearly show the efficiency frontier in the CCR and BCC orientations. Six iterations of DEA modelling were carried out, each using only one of the 6 indicators of macroeconomic freedom as an output and three indicators of human capital as inputs. The countries with the most effective national mechanisms to ensure that human capital losses do not become an obstacle to strengthening macroeconomic freedoms are Cyprus, Czech Republic, Iceland, Ireland, Malta, and Romania. These countries demonstrate “benchmark” efficiency in 6 cases out of 6 calculated. There is also a group of countries that have never been included in the list of “benchmark” countries: Austria, Belgium, Croatia, Estonia, France, Hungary, Greece, Italy, Lithuania, Latvia, Portugal, Serbia, Slovakia, and Spain. We have also identified countries that are “benchmark” not by all parameters, but only by certain ones: Bulgaria – only in terms of the impact of the studied human capital determinants on monetary freedom; Luxembourg – only on investment freedom and financial freedom; Poland – only on investment freedom.

Research hot spots and trends of keratoconus in China: a bibliometric analysis

Objective: To review the studies related to keratoconus in China, investigate research hotspots and development trends in this field, and provide reference for future research. Methods: This is a bibliometrics study. The relevant literature written in Chinese was retrieved from the WanFang DATA and the China National Knowledge Infrastructure, English articles were collected from the Web of Science Core Collection database. Searched for journal articles related to keratoconus VOSviewer software, CiteSpace, and Bibliometrix in the R language were employed to create the knowledge map. The analysis encompassed the distribution of published journals, research collaboration networks of countries/regions, institutions, and authors. Additionally, core authors, high-frequency keyword co-occurrence, keyword topic maps, and keyword emergence time ranking were examined. Results: The study ultimately included 1 100 Chinese articles and 668 English articles. Chinese literature and English literature began to increase in 1997 and 2009, respectively, indicating that the field is currently in a developmental stage. The publications involved 244 Chinese journals and 150 English journals, predominantly in the field of ophthalmology. The United States collaborated the most with China, contributing to 123 articles, followed by other countries such as the United Kingdom and Switzerland. Chinese literature and English literature involved 552 and 883 institutions, respectively. The institution with the highest number of Chinese literature publications was the Eye Institute of Shandong First Medical University (63 papers), while Wenzhou Medical University had the highest number of English literature publications (91 papers). Chinese literature involved 2 435 authors, and English literature involved 2 073 authors. The largest collaboration cluster in Chinese literature was formed by the teams of Xie Lixin and Shi Weiyun, while the Gao Hua team formed the largest cluster in English literature. However, collaboration between authors was primarily limited to within each team. A total of 622 and 1 611 keywords were extracted from Chinese and English literature, respectively. The node centrality of the four Chinese keywords, "keratoconus", "cornea", "corneal transplantation" and "myopia" as well as the three English keywords, "keratoconus", "collagen cross-linking" and "penetrating keratoplasty" was greater than 0.1. "Collagen", "riboflavin", "corneal transplantation" and "ultraviolet A" were identified as common core hotspots and important research topics in Chinese and English literature on keratoconus. Keyword emergence analysis indicated that the keywords with the highest intensity of emergence in Chinese and English literature were "myopia" (13.54) and "penetrating keratoplasty" (9.99), respectively. The longest emergence time was observed for "contact lenses" (1995-2006) and "penetrating keratoplasty" (2003-2014). Conclusions: At present, research on keratoconus in China is on the rise, with research hotspots including pathogenesis, various new surgical methods, and improvement in quality of life. The future research trend mainly focuses on early diagnosis and screening methods, artificial intelligence, biomechanical examination, subclinical keratoconus, and small incision lenticule extraction.

The Practice of Radicalism: A Bibliometric Analysis

This study aims to conduct a bibliometric analysis of the theme of radicalism. This topic has always been the center of attention because radicalism is one of the world's problems or phenomena faced by many countries. By using the Scopus database from 2016 to 2021, concept mapping and clustering related to the theme of radicalism will be seen. The data was collected through a search on the Scopus database with the keyword radicalism. The data analysis focused on cluster analysis, dominant topics, related themes, and mapping of radicalism study topics based on the number of articles visualized and analyzed using VOSviewer software. This research shows that the study of radicalism has five dominant keywords that often appear, namely Radicalism, Islamism, terrorism, Religion, and Identity. This shows that the five topics are the main focus of attention written by most authors. This research contributes to delivering the development and mapping of the study of radicalism as one of the problems in global democracy. Meanwhile, the limitation is that the articles reviewed are only sourced from Scopus, so they do not have comparative data. Therefore, future studies require using a comparative analysis approach that uses a Web of Science (WoS) database.

Voluntary carbon offsets in sustainable aviation research: A bibliometric analysis

There has been much criticism that the aviation industry has become one of the leading causes of greenhouse gas emissions and global warming. Voluntary carbon offsets (VCOs) assist air travellers in reducing their carbon footprint through the purchase of carbon offsets. This paper aims to review the literature on voluntary carbon offsets in the aviation industry to better understand research progress and outline the future research agenda. The study applied a bibliometric analysis of literature retrieved from the Scopus database. The assessment techniques were topic mapping, citation analysis, co-citation, and co-occurrence analysis of keywords with the help of VOSviewer software. The results highlight the most salient discussions and reveal the core themes in this field. The present research contributes a comprehensive understanding of voluntary carbon offsets in the aviation industry through an in-depth bibliographic investigation of articles and identifies notable research trends on this topic.

Analysis of Government Adaptive Capacity: Understanding Research Topic Mapping

Analysis of Government Adaptive Capacity: Understanding Research Topic Mapping

Artificial Intelligence and its Impact on Management Research: A Large-Scale Bibliometric Topic Mapping Analysis of the Interval 2020-2023

Artificial Intelligence and its Impact on Management Research: A Large-Scale Bibliometric Topic Mapping Analysis of the Interval 2020-2023

THE GREEN PORTS FUTURE KNOWLEDGE MAP AND TREND

The purpose of this study is to track the emergence of research related to green ports over time and determine the knowledge map and trends of green port research topics in the future using thematic map bibliometric analysis. This study also provides an overview of the researchers and contributors of research countries in green port research globally. This research provides a comprehensive bibliometric analysis of historical developments and current trends in green port research, by examining 462 articles published from 1991-2023 on the Scopus database. This research uses R studio Cloud bibliometric analysis and biblioshiny package. It was found that there are three phases in green port research, namely the initial stagnation phase (1991-2006), infant growth (2007-2015), and expanding phase (2016-2022), the number of articles increased quite rapidly in the third phase until now. This research also highlights related to authors, contributor countries and it was found that the country of China contributed the most contributor authors compared to other countries, this is because China is a country that places many container ports as the top 10 largest container ports in the world, with a total market share reaching 70% of the global. From this analysis, it is found that the knowledge map and the direction of future topics related to green ports are “sustainable development”, “port development”, “port operation”, “carbon emissions” and “renewable energy resources”, besides that it is also found that there is a direction of the current green port and “smart port” research trends. So, it can be recommended that in the future these topics will be very relevant to develop, the themes of research themes needed include alternative strategies in net zero emission (NZE) in ports in the operational and development aspects of the port.

Development of a Thread-Based Interaction Model to Increase User Connection in Online Communities

This study applies a thread-based interaction model to enhance user connections within online communities, utilizing diffusion and analytical methods. The diffusion approach is employed to implement a thread structure that facilitates structured and focused conversations among users. These threads enable users to engage in discussions that are more organized and relevant to their interests. Furthermore, analytical methods are applied to map topics and connect related threads. Through the use of topic mapping algorithms, users can discover the most relevant threads aligned with their interests, thereby enhancing their engagement and participation within the community. During the experiment, the effectiveness of the interaction model is evaluated by measuring user connection and engagement levels. The research findings indicate that users are more likely to engage in deeper discussions and connect with other users through this approach. By combining the diffusion method for thread structuring and analytical methods for topic mapping, this study contributes to enhancing the ways users connect and interact within online communities.

Creating a Visual Topic Map for Battery Researchers Using a Large Global Open Dataset

Battery related research has gained increasing attention in recent years. A large number of research papers about battery are being published as open access. In order to explore the research content in these papers efficiently, it is necessary to develop information management tools to capture the knowledge embedded in them.We are working on a project to create a visual topic map for battery researchers. This map connects battery researchers according to their research topics. This allows potential connection between researches with similar research topics, which increase collaboration opportunities to advance battery research. Additionally, visualization of research content supports intuitive capturing of research trend by maximizing information absorbance.We extract all published works related to battery research from OpenAlex1, which is a fully open catalog of the global research that offers significant advantages in terms of data coverage and affordability and openness. Anther important feature of OpenAlex is that, every article is tagged with multiple concepts using automatic classifier. In addition to concepts extracted from OpenAlex dataset, we used a pre-trained large language model, named KeyBERT2, to further extract representative terms from the work abstract. KeyBERT is a minimal and easy-to-use keyword extraction technique based on the transformers model.For each researcher, we have extracted all concepts and terms from all the articles that authored by that author. Using those terms and concepts, we formulate a vector for each researcher that represents the total research output. To find researchers with similar research interests, we measure similarity between the vectors in the authors space. Top matching authors are connected visually to create a map expands over representative topics in battery related research. Figure 1 shows a snapshot of this map. Researchers names were hidden for privacy purposes. 1Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. ArXiv. https://arxiv.org/abs/2205.01833 2Grootendorst, M. (2020). KeyBERT: Minimal keyword extraction with BERT. https://doi.org/10.5281/zenodo.4461265 Figure 1

Analysis of Character Education Values in Wewarah Osing

Osing is a native tribe of Banyuwangi located in East Java Province. The Osing tribe owns a variety of unique and interesting cultures to learn about. One of the cultures from the Osing tribe is wewarah Osing. In wewarah Osing, there are many wise words with good character values which are able to strengthen the nation’s character. Therefore, this study aimed to analyze the character values contained in wewarah Osing. The study method applied in this research is a qualitative method through a literature study as the data collection technique. Whereas the research data are obtained through creating a topic mapping in relation to character education and Osing culture found from Google Scholars, Crossref, ResearchGate, related books and journals, accessed from 10 March 2023 to 26 June 2023. The result of the study showed in wewarah Osing, traditional proverbs to support or used to strengthen the national character. These good characters namely discipline, social care, hard work, responsible, and religious.

Quantitative Topic Analysis of Materials Science Literature Using Natural Language Processing.

Materials science research has garnered extensive attention from industry, society, policy, and academia. However, understanding the research landscape and extracting strategic insights are challenging due to the increasing diversity and volume of publications. This study proposes a natural language processing-based protocol for extracting text-encoded topics from a large volume of scientific literature, uncovering research interests of scientific communities, as well as convergence trends. We report a topic map, representing the materials science research landscape with text-mined 257 topics regarding biocompatible materials, structural materials, electrochemistry, or photonics. We analyze the topic map in terms of national research interests in materials science, revealing competitive positions and strategies of active nations. For example, it is found that the increasing trend of research interest in machine learning topic was captured in the United States earlier than other nations. Similarly, our journal-level analyses serve as reference information for journal recommendations and trend guidance, showing that the main topics and research interests of materials science journals slightly changed over time. Moreover, we build the topic association network which can highlight the status and future potential of interdisciplinary research, revealing research fields with high centrality in the network such as machine learning-enabled composite modeling, energy policy, or wearable electronics. This study offers insightful results on current and near-future materials science research landscapes, facilitating the understanding of stakeholders, amidst the fast-evolving and diverse knowledge of materials science.

Perkembangan Penelitian dan Pemetaan Topik pada Riset Sapi Bali berdasarkan Publikasi Jurnal Ilmiah dan Prosiding

Animals that have the potential to produce meat that can be developed are Bali cattle. Unlike imported cattle, Bali cattle are superior because they can withstand all weather and adapt easily. Research on Bali cattle is quite a lot. However, we do not yet know the direction and status of the research. For this reason, it is necessary to conduct a study of the research that has been carried out. The research data comes from secondary data, namely scientific journal articles and proceedings articles. Data publication year is limited to June 2023. Data is tracked using Publish or Perish software. The data obtained was processed using Zotero, MS-Excel and VOSviewer software. There were 983 studies found, with the highest number of animal feed and nutrition, with 190 studies (19.31%). The most productive researcher is Jakaria (49 titles). The number of Bali cattle studies each year varies greatly with the highest number occurring in 2020 (169 studies). It is known that the authorship pattern of the Bali cattle research results article is in accordance with Lotka's law with an exponent value of 2.1 and a constant value of 66%. The researcher collaboration map and research topic map were successfully created using VOSviewer. The degree of author collaboration was 0.91. Related research including animal waste, animal welfare, animal farm and conservation can still be developed because there are not many researches in these fields.

Bibliometric and Co-Occurrence Study of Process System Engineering (PSE) Applied to the Polyvinyl Chloride (PVC) Production.

PVC is widely used in packaging, electrical insulation, and medical devices due to its versatility owing to its resistance, incombustible and barrier properties as well as affordable cost. In the present study, bibliometric and co-occurrence analyses are proposed to identify trends, gaps, future directions, and challenges regarding process system engineering (PSE) applied to the production process of PVC using VOSviewer as a tool for analyzing the data obtained from SCOPUS. A mapping of different topics alluding to simulation of PVC production was provided to gain a better insight into the development of the topic and its progression. The findings indicate that the literature on this topic falls into five different clusters: modeling and simulation of PVC production, process control and optimization, and optimization strategies of the process. From a co-occurrence study we identified that mathematics and statistics applied to polymer chemistry, separation phenomena, and polymer production are the main areas of interest for further research. The trends suggest that Monte Carlo and numerical simulation can contribute to a deeper understanding of PVC's properties and behavior. In addition, the focus on plastics and microplastics reflects concerns about the environmental impact. A bibliometric study evidenced that PSE provides the tools for improvement in PVC production processes by employing advanced process engineering techniques. Modelling and new algorithms for simulation methods of continuous polymerization processes are important to enhance accuracy and efficiency across various applications. The study also proposes a research agenda for future researchers working in the field of the use of PSE applied to the PVC production process.

Analisis Bibliometrik:Keterkaitan antara Triple Helix dan Open Innovation

This research examines the correlation between Triple Helix and Open Innovation. The study aims to determine: (1) the development of the number of international publications related to Triple Helix and Open Innovation from 2003 to 2023; (2) the mapping of topics related to Triple Helix and Open Innovation based on co-word analysis; (3) the collaboration among authors or researchers related to Triple Helix and Open Innovation. Data collection was done by retrieving publication data from Google Scholar using the "publish or perish" approach with the keywords Triple Helix and Open Innovation within the period of 2003-2023. The data were in RIS/Refman format and analyzed using VosViewer software. The results show that the highest growth of publications related to Triple Helix and Open Innovation from 2003 to 2023 occurred in 2018, with 93 publications or 9.31%. The research findings indicate that the topics related to Triple Helix and Open Innovation from 2003 to 2023 can be divided into six clusters. Based on co-occurrence analysis through network visualization and density visualization, it can be concluded that Triple Helix and Open Innovation are interconnected and have been extensively published. For future research, the authors suggest conducting bibliometric analysis on reputable journal databases or those indexed in Scopus that explore the correlation between Triple Helix and Open Innovation. Additionally, it is necessary to conduct practical approaches such as case studies on the correlation between Triple Helix and Open Innovation within the innovation ecosystem in Indonesia