Semantic domain comparison of research keywords by indicator-based fuzzy distances: A new prospect |
| |
| Institution: | 1. Earthquake Research Center, Ferdowsi University of Mashhad, Iran;2. Department of Knowledge and Information Science, Ferdowsi University of Mashhad, Iran;1. College of Economics, Shenzhen University, Shenzhen, Guangdong 518060, China;2. School of Management, Huazhong University of Science and Technology, Wuhan 430074, China;1. College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China;2. School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;3. Business Administration Department, Applied College, Najran University, Najran, Saudi Arabia;4. Shariaa, Educational and Humanities Research Center (SEHRC), Najran University, Najran, Saudi Arabia;5. Department of Industrial & Systems Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, P.O.Box 84428, Riyadh 11671, Saudi Arabia;6. Department of Industrial Engineering, College of Engineering in Al-Qunfudah, Umm Al-Qura University, Makkah 21955, Saudi Arabia;1. INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal;2. University of Coimbra, CISUC, Department of Informatics Engineering, Coimbra, Portugal |
| |
| Abstract: | Assessing the similarity of scientific outputs based on an indicator has not been addressed much so far. The topic, however, may find several potential applications which can help enrich procedures of ranking, research monitoring, and scientific policy-making. The present study offers a new method to quantify such similarities based on keyword co-occurrence matrices. In the proposed method, first, the keyword co-occurrence networks are transformed into their associated newly defined fuzzy sets, named as scientosemantic domains. Then, a fuzzy distance between the two domains is found based on an arbitrary indicator. In this paper, the three indicators of frequency, development and investment appeal are used. The proposed method is implemented for five types of concept comparison. For each type, concepts are represented by a canonical keyword with different field codes. Scientosemantic domains of concepts are sourced out of bibliometric data obtained from appropriate queries on SCOPUS. Number of keywords used to define scientosemantic domains ranges from about 30 to 800. Since indicator-based comparison of scientosemantic domains are not dealt with in the literature, the obtained distances between concepts are verified by qualitative and expert evaluations. For all cases, frequency- and development-based distances are less than those for investment appeal; while crisp distances for the latter extend beyond 0.6, the former does not exceed 0.3. The greatest distances are observed for investment appeal in technology-related keywords. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
