Important Keywords Research Articles

Design thinking for innovation in sustainable built environments: a systematic literature review

PurposeThis systematic literature review investigates the contribution of design thinking (DT) as a process and tool to drive innovation in a sustainable built environment (SBE) and develops a new model for sustainability research integrating DT and future thinking approaches toward achieving a unified DT and foresight notion for future research and applications.Design/methodology/approachThis review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Open-access English articles published between 2000 and 2022 identified using the EBSCOhost, Emerald Insight, DOJA, JSTOR, Scopus and Taylor and Francis database searches were reviewed. The review framework deploys a previously proposed modified Ansoff matrix with an integrated innovation matrix to identify and analyze the challenges and opportunities for innovation growth in SBE. Additionally, a citation analysis was conducted to explore the impact of DT for innovation in SBE, and a proposed framework based on design by drawing on foresight theory was developed.FindingsResearch on DT for innovation in SBE faces the challenge of unanticipated impacts. According to the average number of citations per document, innovation associated with new solutions within a new context seems to become highly influential. Additionally, research gaps exist in the integration of foresight and DT into sustainability research to identify new contexts and solutions to SBE. A model of foresight design thinking (FDT) is proposed to guide future research and support the practical application of DT in sustainability.Research limitations/implicationsThis analysis was limited by the selection criteria as only certain keywords were used and English-only articles were selected. Future research should consider the use of DT for innovation in SBE using various important keywords, which would improve research findings and expand the contribution of DT to SBE.Practical implicationsThe FDT model offers a new holistic framework for the iterative process of reframing and reperception, focusing on divergent and convergent thinking with the goal of contributing to SBE practices.Social implicationsThe integrated framework of DT and foresight can contribute to the study and development of sustainable innovation and a strategic shift toward a sustainable society.Originality/valueThe integration of DT, foresight and sustainability can broaden the horizons of sustainability research by systematically addressing future challenges related to SBE, which can be translated into feasible and innovative solutions. Thus, the FDT model complements the application of DT in sustainable innovation in this research field.

Cryptocurrency as an investment or speculation: a bibliometric review study

PurposeThe study was done to review the existing literature available on the theme using a popular technique known as a bibliometric review. The purpose was to explore important bibliometric trends such as geographical distribution of research; the most relevant countries and institutions and important collaboration networks, frequently published authors, the most relevant topics/research domains and relationships among these, average citations or per year, the most relevant sources, top authors’ production, authors’ impact by H index and the progression of important keywords over a period of time.Design/methodology/approachThe study analyzed literature published in the English language from 2012 onwards that used the words “cryptocurrency”, “Ethereum” “Bitcoin” along with “investment/s” or “speculation/s” in the Title/ABS/KEY. A specialized approach was followed to retrieve and analyze focused research. The data for analysis was extracted from the Scopus database and was analyzed using Biblioshiny and VOSViewer.FindingsThe study found that the countries such as the UK, Australia, China and the USA have special relevance in terms of the number of citations and collaboration networks. Cryptocurrency/Cryptocurrencies, bitcoin have been the base themes along with other crucial issues such as volatility, hedging, COVID-19 pandemic, Ethereum, blockchain, co-integration, portfolio diversification/optimization, spillover, safe haven, investor attention, gold, etc. There is a lot of interdisciplinary research on the theme.Originality/valueThe current study used a concentrated approach to study the bibliometric literature about the financial implications of cryptocurrency as an asset class and not prominently its technological or legal aspects.

An Automated Literature Review Tool (LiteRev) for Streamlining and Accelerating Research Using Natural Language Processing and Machine Learning: Descriptive Performance Evaluation Study.

Literature reviews (LRs) identify, evaluate, and synthesize relevant papers to a particular research question to advance understanding and support decision-making. However, LRs, especially traditional systematic reviews, are slow, resource-intensive, and become outdated quickly. LiteRev is an advanced and enhanced version of an existing automation tool designed to assist researchers in conducting LRs through the implementation of cutting-edge technologies such as natural language processing and machine learning techniques. In this paper, we present a comprehensive explanation of LiteRev's capabilities, its methodology, and an evaluation of its accuracy and efficiency to a manual LR, highlighting the benefits of using LiteRev. Based on the user's query, LiteRev performs an automated search on a wide range of open-access databases and retrieves relevant metadata on the resulting papers, including abstracts or full texts when available. These abstracts (or full texts) are text processed and represented as a term frequency-inverse document frequency matrix. Using dimensionality reduction (pairwise controlled manifold approximation) and clustering (hierarchical density-based spatial clustering of applications with noise) techniques, the corpus is divided into different topics described by a list of the most important keywords. The user can then select one or several topics of interest, enter additional keywords to refine its search, or provide key papers to the research question. Based on these inputs, LiteRev performs a k-nearest neighbor (k-NN) search and suggests a list of potentially interesting papers. By tagging the relevant ones, the user triggers new k-NN searches until no additional paper is suggested for screening. To assess the performance of LiteRev, we ran it in parallel to a manual LR on the burden and care for acute and early HIV infection in sub-Saharan Africa. We assessed the performance of LiteRev using true and false predictive values, recall, and work saved over sampling. LiteRev extracted, processed, and transformed text into a term frequency-inverse document frequency matrix of 631 unique papers from PubMed. The topic modeling module identified 16 topics and highlighted 2 topics of interest to the research question. Based on 18 key papers, the k-NNs module suggested 193 papers for screening out of 613 papers in total (31.5% of the whole corpus) and correctly identified 64 relevant papers out of the 87 papers found by the manual abstract screening (recall rate of 73.6%). Compared to the manual full text screening, LiteRev identified 42 relevant papers out of the 48 papers found manually (recall rate of 87.5%). This represents a total work saved over sampling of 56%. We presented the features and functionalities of LiteRev, an automation tool that uses natural language processing and machine learning methods to streamline and accelerate LRs and support researchers in getting quick and in-depth overviews on any topic of interest.

Research focus and thematic trends of transient receptor potential vanilloid member 1 research: a bibliometric analysis of the global publications (1990-2023).

Recently, various studies have been devoted to the study of transient receptor potential vanilloid member 1 (TRPV1)-related diseases, potential drugs, and related mechanisms. The objective of this investigation was to examine the significant areas and cutting-edge developments in TRPV1 study within recent decades. Articles or reviews were obtained from the Web of Science Core Collection. VOSviewer 1.6.18 and CiteSpace 6.1 R2 software were utilized to examine publication growth, distribution by country/region, institution, journal, authorship, references, and keywords. The software identified keywords with a high citation burstiness to determine emerging topics. From 1990 to 2023, the annual global publications increased by 62,000%, from 1 to 621. Journal of neuroscience published the most manuscripts and Nature produced the highest citations. The USA, Seoul National University and Di marzo V were the most productive and impactful institution, country, and author, respectively. "TRPV1," "Capsaicin receptor," "Activation," and "Pain" are the most important keywords. The burst keywords "TRPV1 channel," "Oxidative stress," "TRPV1 structure," and "Cancer" are supposed to be the research frontiers. The present study offers valuable insights into the understanding of TRPV1 and pain-related conditions. The research on TRPV1 has demonstrated a steady increase in studies related to pain-related diseases in the past few decades. The significance of TRPV1 in cancer pathogenesis and the resolution of its structure will emerge as a new academic trend in this field, providing direction for more widespread and comprehensive studies in the future.

Knowledge sharing and innovation in business organization: A literature review

BACKGROUND: This study is a review of the literature related to the linkage of knowledge sharing and innovation in organizations. This is among the very few studies related to analyzing the extant literature about the relationship between knowledge sharing and innovation to reveal the knowledge gaps and recommend future research directions. OBJECTIVE: The goal of this review of literature is to highlight the most essential concepts that may affect knowledge sharing and innovation, as well as to provide a foundation for future research on knowledge sharing and innovation through bibliometric analysis. The study identifies perhaps the most important popular keywords directly related to knowledge sharing and innovation. METHODS: This study systematically reviews papers on knowledge sharing and innovation extracted from the Web of Science. RESULTS: The study identified the five clusters, each comprising a set of closely related concepts of knowledge sharing and innovation. The first cluster was comprised of the concepts directly revealing the relationship between knowledge sharing and innovation. This stream of research consists of a well developed of research. The other clusters such as knowledge management, innovation performance, mediation processes underlying the relationship between knowledge sharing and innovation also revealed the relationship between knowledge sharing and innovation. IMPLICATIONS: This research has a number of theoretical and practical implications. Theoretically, this study identifies knowledge gaps and new avenues for future research. This study also helps managers and decision makers to identify and examine trends in promoting the linkage between knowledge sharing and innovation.

빅데이터 분석을 이용한 코로나 19 이후 경호 관련 학과의 사회적 인식 분석

Objectives The purpose of this study is to analyze society's overall perception of universities' security-related departments through big data, provide basic data for the development of security-related departme.
 Methods Under the keyword “University + Security,” data from major domestic portal sites were collected and refined from January 20, 2020 to March 31, 2023, when the first COVID-19 confirmed case in Korea was found, and word cloud analysis, network analysis and centrality analysis, and CONCOR analysis were conducted.
 Results First, through word cloud analysis of the top 30 keywords of frequency, ‘police’ was found to be an overwhelmingly frequent keyword. Second, in network analysis, “police” was confirmed to be the most important keyword, and words such as “police”, “security”, “administration”, “major”, and “sports” showed high connectivity in connection centrality analysis. In the mediation centrality analysis, it was confirmed that most keywords serve as bridges between nodes and are actively connected. Third, in the CONCOR analysis, it was confirmed that it was clustered into six groups, and the cluster name was determined as ‘public security and After Graduation’, ‘Curriculum and Employment’, ‘University Promotion’, ‘physical education’, ‘Daegu’, and ‘Other’.
 Conclusions It was confirmed that the police and security have a close relationship in people's perceptions, and it is believed that it would be a desirable direction to properly utilize them and reflect them in security-related departments. IIt is necessary to develop and apply a curriculum that can strengthen the systematicity of education and enhance expertise to induce students' interest. It is necessary to use it as an advantage of security-related departments by increasing positive awareness and interest in bodyguards, and it will be helpful to prepare and present specific plans for students' careers and post-graduation plans, and to find and advance to public security.

Implementation of the Problem Based Learning Model in Science Education: Trend and Opportunity of Research Using Systematic Literature Network Analysis

The purpose of this study is to describe research trend data related to the implementation of PBL in science education. Article metadata was collected from the SCOPUS database, and 131 relevant articles were selected in 2013-2022. Data were analyzed using the Systematic Literature Network Analysis (SLNA) method with the VOSViewer application. Variables of bibliometric analysis, such as the number of articles and citations each year, the journals and authors with the most publications, countries, and networks of authors' cooperation, were determined based on metadata and analyzed descriptively. This research shows that the number of PBL research articles in science education during the 2013-2022 period fluctuated and tended to increase. The top keywords with the highest link strength are science, teacher, and technology. Recent research focuses on modules/e-modules, scientific literacy, natural science, and physics as important keywords. Future research related to the use of PBL learning has the potential to be developed in physics material and focuses on developing 21st-century skills such as creative thinking, critical thinking, communication, and collaboration. In addition, further research can focus on developing the knowledge and skills of prospective teachers in implementing PBL models that are integrated with 21st-century skills.

Navigation of Knowledge: the Impact of COVID-19 on Pregnancy-a Bibliometric Analysis.

Since the outbreak of COVID-19, countries around the world have faced huge economic and social burdens. SARS-COV-2 may exist in nature for a long time due to the diversity of its different variants. Pregnant women and newborns as vulnerable groups will suffer serious health threats. Bibliometrics as a method of summarizing publications can be used to extract important achievements and hot topics in this field. We search the target publications from the Web of Science Core collection database, and then use Microsoft Office Excel, CiteSpace, R, Scimago, and VOSviewer for visual analysis. Finally, we included 1709 publications from 2998 institutions in 104 countries. The number of publications has exploded since the COVID-19 pandemic in 2019. Among them, the USA, China, Britain, and Italy have higher quantity and quality. We identified important journals, authors, keywords, and references in this field. Anxiety, stress, risk of pregnancy complications, and vaccine safety and acceptance have received extensive attention from scholars during the COVID-19 pandemic and will continue to be urgent issues to be addressed in the future. Most of the current studies fall into the category of case reports and clinical data analysis. COVID-19 has been linked to serious pregnancy complications and mental illness, and vaccination during pregnancy is recommended to protect both mother and fetus. Further large-scale cohort studies and discovery of molecular mechanisms are needed in this field.

Worldwide Research Trends for Chelates in Animal Science: A Bibliometric Analysis.

The purpose of this study was to look at research trends in the application of CTM in animal nutrition in order to identify current and emerging challenges, as well as to examine the intellectual structure of the subject. The intellectual structure of CTM was examined using keyword and reference analysis. The research community includes all research and review articles published in journals indexed in the Web of Science database during the years 1990-2022. The results showed that the terms zinc, co-occurring 331 times, performance (324 times), and copper 216 (times) were the main and hotspots of research in the field of chelate. The data suggest that the most important keywords during the study period were zinc, copper, pig, bovine, metabolism, and bioavailability. The terms health, muscle, beef, trace elements, and dietary supplements represent emerging topics in CTM, as research began to focus on these areas during the years 2017-2022. The country with the greatest number of published articles was the United States of America. This bibliometric analysis showed that countries are focusing on the effects of CTM on the health and musculature of cattle through dietary supplementation with trace elements. According to the identified hot and emerging topics, this research can serve as a roadmap for a global comprehensive scientific plan and policy.

Comprehensive bibliometric research in neuroscience: focusing on ophthalmology.

This study aimed to comprehensively summarize the knowledge structure and research hotspots of ophthalmology in the field of neuroscience through bibliometric and visual analysis. We searched the Web of Science Core Collection database for articles from 2002 to 2021 related to ophthalmology in the field of neuroscience. Using VOSviewer and CiteSpace, bibliometric analysis was conducted on the number of annual ophthalmology publications, authors, organizations, countries, journals, cited references, keywords, and burst keywords. A total of 9,179 articles were published from 34,073 authors, 4,987 organizations, and 87 countries. The cited references in these articles were published in 23,054 journals. Moreover, there were 30,864 keywords among the 9,179 articles. Notably, scholars have increasingly begun paying attention to ophthalmology in the field of neuroscience in the past 20 years. Claudio Babiloni published the most articles. The University of Washington had the greatest number of articles. The United States, Germany, and England led in the number of articles published. The Journal of Neuroscience was the most cited. The article with the highest outbreak intensity was an article published by Maurizio Corbetta in Nature Reviews Neuroscience in 2002 entitled "Control of goal-directed and stimulus-driven attention in the brain." The most important keyword was the brain, and the top burst keyword was functional connectivity. This study visualized ophthalmology research in the field of neuroscience through bibliometric analysis and predicted potential research trends in future to help clinicians and basic researchers provide diversified perspectives and further carry out in-depth research on ophthalmology.

Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarity in Online Public Discourse

With the growth of online news over the past decade, empirical studies on political discourse and news consumption have focused on the phenomenon of filter bubbles and echo chambers. Yet recently, scholars have revealed limited evidence around the impact of such phenomenon, leading some to argue that partisan segregation across news audiences can- not be fully explained by online news consumption alone and that the role of traditional legacy media may be as salient in polarizing public discourse around current events. In this work, we expand the scope of analysis to include both online and more traditional media by investigating the relationship between broadcast news media language and social media discourse. By analyzing a decade’s worth of closed captions (2.1 million speaker turns) from CNN and Fox News along with topically corresponding discourse from Twitter, we pro- vide a novel framework for measuring semantic polarization between America’s two major broadcast networks to demonstrate how semantic polarization between these outlets has evolved (Study 1), peaked (Study 2) and influenced partisan discussions on Twitter (Study 3) across the last decade. Our results demonstrate a sharp increase in polarization in how topically important keywords are discussed between the two channels, especially after 2016, with overall highest peaks occurring in 2020. The two stations discuss identical topics in drastically distinct contexts in 2020, to the extent that there is barely any linguistic overlap in how identical keywords are contextually discussed. Further, we demonstrate at-scale, how such partisan division in broadcast media language significantly shapes semantic polarity trends on Twitter (and vice-versa), empirically linking for the first time, how online discussions are influenced by televised media. We show how the language characterizing opposing media narratives about similar news events on TV can increase levels of partisan dis- course online. To this end, our work has implications for how media polarization on TV plays a significant role in impeding rather than supporting online democratic discourse.

The Place of Lifelong Learning in the Paidia Curriculum

Lifelong learning has become an important keyword in international research and studies because of its increasing impact on educational policies globally. One of the important goals of education systems worldwide is lifelong learning. The research method is descriptive-analytical. Data collection is in the form of extracting data from Adler's books, the second category of resources related to the Paidia curriculum. The method of data analysis was classification and interpretation, which was done simultaneously with data collection. In this descriptive-analytical study, Mortimer Adler's educational thinking has been analyzed in the context of Paideia, and the relationship between public education and continuous learning has been examined. According to the research findings, according to Adler, the public education curriculum underpins lifelong learning, and after school education, any failure in lifelong learning constitutes a failure in public education, while continuing learning. It can improve the health of students in adulthood. On the other hand, vocational education has no place in the Paideia curriculum. If, in the light of the critique of the plan, a stronger foundation for lifelong learning can be hoped for, given the place of work and profession in the field of public education. It is recommended that in future research, researchers compare Adler's perspective on continuous learning with other thinkers. One of the most important limitations of the current research was the lack of access to schools that were designed based on the Paidia program. Another suggestion for future research is to examine the schools that have been established based on the Paidia program and study the continuous learning process in them.

Role of Gene Mutations in Acute Myeloid Leukemia: A Review Article

AbstractAcute myeloid leukemia (AML) is an immensely heterogeneous disease characterized by the clonal growth of promyelocytes or myeloblasts in bone marrow as well as in peripheral blood or tissue.Enhancement in the knowledge of the molecular biology of cancer and recognition of intermittent mutations in AML contribute to favorable circumstances to establish targeted therapies and enhance the clinical outcome. There is high interest in the development of therapies that target definitive abnormalities in AML while eradicating leukemia-initiating cells. In recent years, there has been a better knowledge of the molecular abnormalities that lead to the progression of AML, and the application of new methods in molecular biology techniques has increased that facilitating the advancement of investigational drugs.In this review, literature or information on various gene mutations for AML is discussed. English language articles were scrutinized in plentiful directories or databases like PubMed, Science Direct, Web of Sciences, Google Scholar, and Scopus. The important keywords used for searching databases is “Acute myeloid leukemia”, “Gene mutation in Acute myeloid leukemia”, “Genetic alteration in Acute myeloid leukemia,” and “Genetic abnormalities in Acute myeloid leukemia.”

Capturing New Nurses' Experiences and Supporting Critical Thinking: Text Network Analysis of Critical Reflective Journals.

This study analyzed the contents of critical reflective journals written by new nurses during their orientations using a text network. This study aimed to find ways to reduce turnover and improve clinical field adaptability among new nurses. The authors analyzed the content of reflective journals written by 143 new nurses from March 2020 to January 2021. Text network analysis was performed using the NetMiner 4.4.3 program. After data preprocessing, frequency of occurrence, degree centrality, closeness centrality, betweenness centrality, and eigenvector community were analyzed. In total, 453 words were extracted and refined, and words with high simple frequency and centrality were "incompetence," "preparation," "explanation," "injection," "time," "examination," and "first try." "Medication" had the highest frequency of occurrence, and "incompetence" was the most important keyword in the centrality analysis. In addition, component analysis and eigenvector community analysis revealed three sub-theme groups: (1) basic nursing skills required for new nurses, (2) insufficient competency, and (3) explanation of nursing work. Significantly, this study is the first to use the text network method to analyze the subjective experiences of the critical reflective journals of new nurses. In conclusion, changes are needed to improve the education system for new nurses and promote efficient sharing of nursing tasks.

СТОРІТЕЛІНГ ЯК ЗАСІБ АКТИВІЗАЦІЇ ПІЗНАВАЛЬНОЇ АКТИВНОСТІ УЧНІВ У СУЧАСНОМУ ОСВІТНЬОМУ ПРОСТОРІ

This article investigated the use of storytelling in teaching technology and foreign literature in school. Storytelling is not just about literary stories, but rather about effectively transferring information and motivating action through storytelling. It is used in many fields such as interpersonal communication, media, business, advertising, politics, education, and art. The value of content, word beauty, and form refinement are still important in storytelling. Storytelling is a teaching tool for centuries, and it continues to be an effective method for engaging students in learning. In recent years, educators have begun to explore the use of storytelling specifically in teaching technology and foreign literature in schools. Today storytelling has become widespread educational method. Stories can be used in writings or orally, through different illustrations etc. It also helps to introduce foreign literature to students. By telling stories about the culture and history of the author or the setting of the story, students can gain a deeper understanding of the text. This approach can also help students connect with the material emotionally, which can enhance their engagement and retention. Storytelling in technology or vocational education classes helps launch creative projects for students, promotes motivational components of project-based learning, and activates exploratory and research activities in studying manufacturing technologies. In both cases, storytelling can be used in a variety of ways. Teachers might read stories aloud to the class, ask students to create their own stories, or incorporate storytelling into group projects. The key is to use storytelling as a tool to enhance learning, rather than as a distraction from it. Overall, storytelling can be an effective tool for teaching technology and foreign literature in schools, helping to engage students and deepen their understanding of these important subjects Key words: storytelling, foreign literature, teaching, technology, education

특허분석을 통한 라틴아메리카지역의 유망 공백물류기술 도출

In recent years, the lack of relevant technological infrastructure for innovation in logistics technology in Latin American nations with significant economic expansion has been a factor impeding economic growth. In this case, even though Latin American nations are actively pursuing policies to revive technical innovation, there is an issue with the absence of objective data for policy formation. We suggests a strategy for revitalizing technical innovation through the utilization of promising vacant technologies predicted by patent data analysis. Using GTM, ARIMA, technology mapping, and decision tree analysis, promising vacant technology groups and technological keywords were identified from 670 logistics-related patents extracted between 2010 and 2020. As a result of the investigation, “Multimodal Transportation” and “Simulation-Based Distribution Optimization” derived based on important technology keywords, is perceived as a required technology to revitalize technological innovation in Latin American nations with large territories. The research results can be used as objective data for policymaking to stimulate technical innovation, contributing to more objective policymaking in Latin American countries.

Extended Bibliometric Review of Technical Challenges in Mariculture Production and Research Hotspot Analysis

The growth in population and the higher need for aquatic products make the aquaculture industry the world’s fastest-growing food industry. With its rapid development, production is facing various challenges to achieve sustainability and cost-effectiveness. Some obstacles in production are related to the design of mariculture cages, automatization, location of the farm, biofouling, feeding, waste management, and others. This paper deals with the extended bibliometric analysis of technical problems in mariculture based on keywords, citations, journals, and other factors by means of scientometric software, CiteSpace, and VOSviewer. Important keywords related to aquaculture and mariculture were obtained from the Web of Science platform and further analyzed by means of the mentioned scientometric software offering knowledge domain visualization and construction of knowledge maps. Apart from the identification of research topics of the highest importance, research hotspots are characterized as follows: technical, biological, digital, and environmental. The most cited articles are related to the environmental problems and solutions in marine aquaculture and the study of biofouling and how to control it. Other important documents with high citation rates are related to the cages, offshore mariculture, location conditions, and sustainability. This study recognizes trends by combining aquaculture production with floating structures for energy extraction of sea resources; thus, making aquaculture more interdisciplinary than before.

Role of Molecular Targeted Therapeutic Drugs in Treatment of Breast Cancer: A Review Article.

Breast cancer is a multifactor, multistage, and heterogeneous disease. Systemic treatment of breast cancer has changed significantly over the last decade. With a better knowledge of the pathogenesis, researchers and scientists have discovered numerous signaling pathways and synonymous therapeutic targets in breast cancer. Because of the molecular nature of breast cancer, which makes it difficult to understand, previous attempts to treat or prevent it have failed. However, recent decades have provided effective therapeutic targets for treatment. In this review, literature or information on various targeted therapy for breast cancer is discussed. English language articles were explored in numerous directory or databases like PubMed, Web of Sciences, Google Scholar, ScienceDirect, and Scopus. The important keywords used for searching databases are "Breast cancer," "Targeted therapy in breast cancer," "Therapeutic drugs in breast cancer," and "Molecular targets in breast cancer."

66. Narrative Letters of Recommendation and Match Outcomes: How Words Differentiate Applicants

PURPOSE: Letters of recommendation (LORs) are an essential component of residency applications. As grades and Step scores have become pass/fail, programs have fewer objective measures to assess applicants. As a result, even greater emphasis may be given to LORs in residency applications. This study aims to evaluate the role of narrative LORs in Match outcomes. METHODS: From the 2020-21 Match, one hundred first-time applicants from US medical schools were randomly selected. Application characteristics and the narrative LOR text were collected from residency applications. Match outcomes and LOR author demographics were determined from publicly available data. Characteristics of LOR text, such as word count (WC) and word frequency percentages, were calculated using the linguistics software Linguistic Inquiry and Word Count 2015. A bag-of-words classification model designed in Matlab R2022b was used to predict Match outcomes based purely on word frequency variation. The text of 299 LORs was used to train the model, and its accuracy was assessed with 52 LORs. The bag-of-words classification model also identified the words most likely to predict Match outcomes, which were termed “differentiation words.” RESULTS: Of the one hundred applicants included in this study, 69% of applicants matched into a PGY-1 plastic surgery residency position. Although most (57%) applicants were female, only 18.7% of letter writers were female. On average, female applicants had LORs with higher WCs (453 vs. 417, p=0.0497). Additionally, female letter writers wrote higher WC LORs for applicants (475 vs. 429, p=0.045). No differences in WC were observed based on academic rank. For applicants who successfully matched, their LORs averaged a significantly higher WC (463 vs. 375, p<0.0001). The bag-of-words classification model was able to predict outcomes based on the LOR text alone with an accuracy of 91.4%. The word frequency of “differentiation words” was also significantly higher in the LORs of those who matched (2.59% vs. 2.22%, p=0.002). CONCLUSIONS: These results demonstrate that even in the absence of numeric data such as Step 1 scores and publication metrics, the written language in LORs can stratify applicants. This work suggests that highly descriptive and positive adjectives such as “bright” and “excellent” are important keywords for evaluators to include in LORs to indicate applicant strength. Finally, plastic surgery programs may consider using machine learning algorithms to assess LORs, not only to save residency programs time but also to mitigate individual reviewer bias.

Changes in Keywords Related to Housing Stress Before and After COVID-19 Using Big Data Analysis - Focusing on newspaper articles during 2018~2022 -

The purpose of this study was to explore keyword changes related to housing stress before and after the outbreak of COVID-19 using big data analysis methodology. Newspaper articles for 4 years before and after COVID-19 were collected in relation to housing stress from Naver News platform, and 27,898 keywords were extracted. The collected data was refined using R4.2.2 program and analyzed using vocabulary usage frequency analysis, Odd ratio analysis, Phi analysis, Semantic Network Analysis, and Topic Modeling. Major findings are as follows. 1) After COVID-19, the frequency of occurrence of the keyword ‘residential environment’ was the highest, and ‘housing complex’ was the most important keyword in the semantic network results. 2) The keyword ‘bathroom’ was very highly appeared after COVID-19, reflecting the increased interest in hygiene, health, and safety. 3) As remote education, telecommuting, and care within a dwelling have expanded due to COVID-19, the need for more space and flexible housing planning to accommodate them has been highlighted. 4) While COVID-19 has made daily life more difficult for the vulnerable, it has been confirmed that single-parent households were particularly stressed about housing. 5) The housing stress of young people continued to be at a high level before and after COVID-19. 6) It was confirmed that the increase in housing cost was the main factor causing housing stress.