• Title/Summary/Keyword: Scientometric analysis

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Sentiment Analysis and Opinion Mining: literature analysis during 2007-2016 (감정분석과 오피니언 마이닝: 2007-2016)

  • Li, Jiapei;Li, Xiaomeng;Xiam, Xiam;Kang, Sun-kyung;Lee, Hyun Chang;Shin, Seong-yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.160-161
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    • 2017
  • Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language Opinion mining and sentiment analysis(OMSA) as a research discipline has emerged during last 15 years and provides a methodology to computationally process the unstructured data mainly to extract opinions and identify their sentiments. The relatively new but fast growing research discipline has changed a lot during these years. This paper presents a scientometric analysis of research work done on OMSA during 2007-2016. For the literature analysis, research publications indexed in Web of Science (WoS) database are used as input data. The publication data is analyzed computationally to identify year-wise publication pattern, rate of growth of publications, research areas. More detailed manual analysis of the data is also performed to identify popular approaches (machine learning and lexcon-based) used in these publications, levels (documents, sentences or aspect-level) of sentiment analysis work done and major application areass of OMSA.

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Technology Convergence Map Creation and Country Profile Analysis in the Field of Artificial Intelligence (인공지능 분야의 기술융합맵 생성 및 국가 프로파일 분석)

  • Kim, Hyun-Woo;Noh, Kyung-Ran;Ahn, Sejung;Kwon, Oh-Jin
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.1
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    • pp.139-146
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    • 2017
  • The interest about Artificial Intelligence through the AlphaGo Match in Korea has been increasing rapidly. So far, very little has been done in Artificial Intelligence. The aim of this paper is to reveal technology convergence and to assess the country profile in the field of artificial intelligence(AI). Technology convergence map was created after extracting USPTO patent grants and Web of Science data and generating matrics in the field of AI. Several Indicators were obtained by extracting and calculating SCOPUS Data that KISTI has. According to USPTO patent grants, it shows that AI technology has a strong relationship with several sectors such as cost/price determination, image analysis, and surgery, etc. Also, AI has a active convergence with some fields of Electrical and Electronic Engineering, BioTechnologies, and Medicine etc. According to country profile analysis, Korea reaches a global average growth index. However, in terms of specialization index (SI) and average of relative citations (ARC), there is a large gap between Korea and research leading countries.

Discovering locally customized and future promising industries using patent analysis : Centered on the Case of Busan city (특허 분석을 통한 지역맞춤형 미래유망산업 발굴 및 도출에 관한 연구 : 부산 지역 사례를 중심으로)

  • Kim, Hyun-Woo;Shim, We;Kwon, Oh-Jin;Noh, Kyung-Ran
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.1
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    • pp.129-138
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    • 2017
  • The aim of this paper is to suggest methodology for local governments when discovering locally customized future promising industries with regard to policies of central government, regional competencies, and industrial promising. Firstly, key industries by region specified in '5-years regional industrial development master plan(2014)' were utilized. Secondly, science and technology competency by region was calculated with analyzing patent data in each key industries. Thirdly, industrial promising was verified by calculating Knowledge Stock and Activity Index based on measuring industry-IPC linkage. Based on the methodology proposed above, case study(case of Busan city) was done. Finally, 7 core industries and 94 candidates of future promising industries were extracted on the basis of 5 digit of KSIC subdivision. The methodology is expected to contribute local governments to establish evidence-based, efficient, and future-oriented local R&D roadmapping.

The Evaluation of Web Contents by User 'Likes' Count: An Usefulness of hT-index for Topic Preference Measurement

  • Song, Yeseul;Park, Ji-Hong;Shim, Jiyoung
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.2
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    • pp.27-49
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    • 2015
  • The purpose of this study is to suggest an appropriate index for evaluating preferences of Web contents by examining the h-index and its variants. It focuses on how successfully each index represents relative user preference towards topical subjects. Based on data obtained from a popular IT blog (engadget.com), subject values of the h-index and its variants were calculated using 53 subject categories, article counts and the 'Likes' counts aggregated in each category. These values were compared through critical analysis of the indices and Spearman rank correlation analysis. A PFNet (Pathfinder Network) of subjects weighted by $h_T$ values was drawn and cluster analysis was conducted. Based on the four criteria suggested for the evaluation of Web contents, we concluded that the $h_T$-index is a relatively appropriate tool for the Web contents preference evaluation. The $h_T$-index was applied to visually represent the relative weight (topic preference by user 'Likes' count) for each subject category of the real online contents after suggesting the relative appropriateness of the $h_T$-index. Applying scientometric indicators to Web information could provide new insights into, and potential methods for, Web contents evaluation. In addition, information on the focus of users' attention would help online informants to plan more effective content strategies. The study tries to expand the application area of the h-type indices to non-academic online environments. The research procedure enables examination of the appropriateness of the index and highlights considerations for applying the indicators to Web contents.

A Scientometric Social Network Analysis of International Collaborative Publications of All India Institute of Medical Sciences, India

  • Nishavathi, E.;Jeyshankar, R.
    • Journal of Information Science Theory and Practice
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    • v.8 no.3
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    • pp.64-76
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    • 2020
  • Scientometrics and social network analysis (SNA) measures were used to analyze the international scientific collaboration (ISC) of All India Institute of Medical Sciences (AIIMS) for a period of 10 years (2009-2018). The dataset consists of 19,622 records retrieved from the Scopus database. The mean degree of collaboration 0.95 implied that researchers of AIIMS tend to collaborate domestically (80.29%) and internationally (14.67%). The data exhibits a hyper authorship pattern, and a medium-size research team consists of 4 to 10 authors who contributed a maximum of 62.08% (12,182) publications. 71.97% of research findings are scattered in journal articles. The most preferred journals published 58.55% of medical literature. An undirected collaboration network is constructed in Pajek to study the ISC of AIIMS during the period 2009-2018 which consists of 179 vertices (Vn) and 11,938 edges. The degree centrality (Dc) identified that the United States of America (Dc - 54; CC - 0.99) and United Kingdom (Dc - 41; 0.98) are the most collaborative countries in the whole network as well as the most influential countries. The Louvain community detection method is used to detect influential research groups of AIIMS. The temporal evolution of ISC of AIIMS studied through scientometrics and SNA measures shed light on the structure and properties of ISC networks of AIIMS. It revealed that AIIMS, India has taken keen steps to enrich the quality of research by extending and encouraging the collaboration between institutions and industries at the international level.

Contemporary research trends on nanoparticles in endodontics: a bibliometric and scientometric analysis of the top 100 most-cited articles

  • Sila Nur Usta ;Zeliha Ugur-Aydin ;Kadriye Demirkaya;Cumhur Aydin
    • Restorative Dentistry and Endodontics
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    • v.48 no.3
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    • pp.27.1-27.11
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    • 2023
  • Objectives: Advancements in nanotechnology have led to the widespread usage of nanoparticles in the endodontic field. This bibliometric study aimed to determine and analyze the top 100 most-cited articles about nanoparticles in endodontics from 2000 to 2022. Materials and Methods: A detailed electronic search was conducted on the "Clarivate Analytics Web of Science, All Databases" to receive the most-cited articles related to the topic. Articles were ranked in descending order based on their citation counts, and the first 100 were selected for bibliometric analysis. Parameters such as citation density, publication year, journal, country, institution, author, study design, study field, evidence level, and keywords were analyzed. Results: The top 100 most-cited articles received 4,698 citations (16-271) with 970.21 (1.91-181) citation density in total. Among decades, citations were significantly higher in 2011-2022 (p < 0.001). Journal of Endodontics had the largest number of publications. Canada and the University of Toronto made the highest contribution as country and institution, respectively. Anil Kishen was the 1 who participated in the largest number of articles. The majority of the articles were designed in vitro. The main study field was "antibacterial effect." Among keywords, "nanoparticles" followed by "Enterococcus faecalis" were used more frequently. Conclusions: Developments in nanotechnology had an impact on the increasing number of studies in recent years. This bibliometric study provides a comprehensive view of nanoparticle advances and trends using citation analysis.

A Study on the Emerging Technology Detection in the Field of LED Using Scientometrics (과학계량학적 정보분석을 통한 LED 및 광분야 유망기술 탐색에 관한 연구)

  • Chang, Si-Young;Lee, Byoung-Chul;Kim, Yun-Bae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.3
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    • pp.1213-1222
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    • 2011
  • The aim of this research is to map the intellectual structure of the field of LED and optics during the period of 2000-2009. We utilize the scientometric tool of co-word analysis to reveal patterns and trends in the LED and optics field by measuring the association strengths of keywords (or IPCs). Data were collected from Science Citation Index Expanded (SCIE) and United Stated Patent and Trademark Office (USTPO) for the period of 2000-2009. Keywords were extracted from abstracts and further standardized using thesaurus. In order to trace the dynamic changes of the LED and optics field, the whole 10-year period was separated into two consecutive periods: 2000-2004 and 2005-2009. The results show that the LED and optics field has some established research themes and it also changes to embrace new themes.

A Scientometric and Meta-analysis of Rail Infrastructure in Nigeria

  • Awodele, Imoleayo Abraham;Mewomo, Modupe Cecilia
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.960-966
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    • 2022
  • Mobility is an essential human need. Human survival and societal interaction depend on the ability to move people and goods. Efficient mobility systems are essential facilitators of economic development. Cities could not exist and global trade could not occur without systems to transport people and goods cheaply and efficiently. Rail has been considered as one of the important components of the transportation infrastructure required to service and improve the performance and productivity of an economy. In Nigeria, the rail infrastructure built by the colonial master several decades ago has been left in a state of total deterioration. This long neglect was occasioned by the failure of the government to pay adequate attention to infrastructure development. There is a vital and urgent need for rail infrastructure development in Nigeria. This study presents a systematic review of the evolution of rail, the current nature of railway infrastructure delivery in Nigeria, and offers possible suggestions on how to achieve an effective and sustainable rail infrastructure delivery in Nigeria. A thorough literature search of academic databases was conducted on current research trends on the subject of railway infrastructure by systematically reviewing selected published articles from reputable research domains. The analysis of the selected articles revealed the following among others (1) the existing railway infrastructure is in a state of mess and not sustainable, and (2), Government's investment/commitment in rail infrastructure seems inadequate compared to what is obtainable in other developed countries. Rail infrastructure development cannot be left to the Federal government of Nigeria to solve on its own; collaboration and participation are required. Government as a matter of priority should devote considerable attention to the development of rail infrastructure to harness the economic potential and transformation that sustainable rail infrastructural projects will provide.

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Scientometric Analysis for Low Carbon Energy (저탄소 에너지 학술 정보 분석)

  • Oh, Mihn-Soo;Kil, Sang-Cheol;Cho, Jin-Dong
    • Economic and Environmental Geology
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    • v.49 no.1
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    • pp.53-61
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    • 2016
  • The lifestyle of human's lives in the current society, it requires a tremendous amount of energy. In the recently, the international community has been progressing the energy technology revolution to combat the resource depletion, energy security and global warming. According to the academic literature to the low-carbon energy(2001~2015) by the program of 'Web of Science', the research activities of 869 papers are to be closely related to low-carbon energy. International joint research on low-carbon energy technologies was mostly conducted by the research center of the United Kingdom, China, the United States, the Netherlands and Japan.

Exploring Convergence R & D area via Data-driven Tech mining: The case of landslide prevention technology linked to ICT (데이터 기반 테크마이닝(tech-mining)을 통한 융합 R&D 영역 탐색: ICT 기반 산사태 예방 기술 사례를 중심으로)

  • Choi, Jaekyung;Seo, Seongho;Kang, Jongseok;Chung, Hyunsang
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.5
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    • pp.483-490
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    • 2019
  • Due to the high complexity and diversity of the problems of the future society, it is getting harder to solve with the traditional single technology. In recent years, there has been a growing interest in convergence technology, which combines or connects different types of technologies to create new technologies and industries. In this study, we explored the convergence R&D area of ICT technology related to landslide prevention/response. It is true that the world has been exposed to various disasters due to recent climate change. As a result, there is a tendency to use Big Data and ICT for disaster preparedness and recovery. Especially, in the case of landslides, it is a natural disaster that requires research not only to study actual landslides but also to predict potential landslides. Therefore, in this study, we analyzed what kind of convergence R&D is being carried out in the field of ICT for preventing and responding to landslide. Therefore, in this study, Web of Science article data were analyzed by using the scientometric analysis and 51 landslide-related ICT convergence R&D areas were derived.