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Analytical Comparison of Iranian Scientific Documents in Text Mining
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Mohadeseh Rafiee *    , Abdalsamad Keramatfar |
| SID, Academic Center for Education, Culture and Research (ACECR), Tehran, Iran , Mohadeseh.rafie2012@gmail.com |
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Abstract: (2410 Views) |
Background and aim: Policymakers seek to evaluate their country's scientific performance and measure it in terms of effectiveness and problem-solving. The aim of this study was to make an analytical comparison of Iranian scientific documents in text mining based on domestic and foreign databases.
Materials and methods: The present study is descriptive survey with a bibliometric approach. In order to find scientific documents related to text mining in the Scopus database, related terms were searched, and then the results were limited to Iran. Scientific Information Database (SID) was used to search for Persian scientific documents. Bibexcel, VOSviewer, Python programming language, and Excel 2017 were used to analyze the data.
Findings: The total number of Iranian scientific documents in text mining in the Scopus citation database was 1082 and 284 (26.25%) of scientific documents indexed in Scopus were in Persian. Moreover, according to the Scientific Information Center, the number of scientific documents in this field was 89 and the number of scientific documents in Persian was 51 (57.30%). The Journal of Lecture Notes in Computer Science has published most international scientific papers in Iran, and the Journal of Signal and Data Processing has published most domestic scientific papers in Iran in text mining. A t-test was used to determine that there was a significant difference in the number of scientific documents in Persian between Scopus and SID databases (p<0.0001).
Conclusion: The average growth rate of Iranian scientific documents in text mining was higher than in other subject areas. The United States, Britain, and Australia have had the most collaboration with Iranian researchers in this field. It was also found that international scientific documents in English received more citations than scientific documents in Persian. |
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| Keywords: Data mining, Text mining, Evaluating science, Bibliometrics, Natural language processing |
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Full-Text [PDF 1051 kb]
(1266 Downloads)
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Type of Study: Orginal |
Subject:
Scientific Production
Received: 2020/08/23 | Revised: 2022/06/26 | Accepted: 2022/07/2 | ePublished: 2022/07/17
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