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https://ah.lib.nccu.edu.tw/handle/140.119/136923| 題名: | 傳統引文指標與Altmetrics指標之比較研究：以諾貝爾生理學或醫學獎得主之研究著作為例 A Comparison Study of Citation and Altmetrics Indicators: The Case Study of the Nobel Prize Laureates in Physiology or Medicine |
作者: | 董冠麟 Tung, Kuan-Lin |
貢獻者: | 蔡明月 Tsay, Ming-Yueh 董冠麟 Tung, Kuan-Lin |
關鍵詞: | 資訊計量學 替代計量學 傳統引文指標 替代計量指標 Informetrics Altmetrics Citation indicators Altmetrics indicators |
日期: | 2021 | 上傳時間: | 2-Sep-2021 | 摘要: | 量化的學術評鑑方法主要透過資訊計量分析與引用文獻分析來評估研究產出，並發展多種指標作為評估的標準，傳統的評鑑指標包含期刊層級的期刊影響係數，論文層級的文獻被引用次數或平均被引用次數，作者層級的h指數等。然而在Web 2.0與開放取用的時代，學術傳播不再侷限於過去的形式，部落格或社群媒體已成為常見的學術交流場域。在這樣的環境下，僅透過傳統引文指標衡量學術研究難以完整地評估其影響力，因此，在2010年出現了Altmetrics的概念，係指基於線上工具與線上環境活動之學術影響計量。\n本研究旨在比較與分析傳統引文指標與Altmetrics指標，並探索兩者之關聯性，本研究以21世紀諾貝爾生理學或醫學獎50位得主的研究著作為對象，採用論文層級與期刊層級的傳統引文指標，來自兩大集成商Altmetric.com與Plum Analytics的Altmetrics指標，以及Web of Science的使用指標與Mendeley的讀者數指標等30種指標，並透過相關性分析、主成分分析、集群分析等統計方法針對上述指標進行分析。研究結果顯示：（1）文獻在Web of Science、Scopus、Dimensions三種綜合學科的引文索引資料庫的被引用樣態相似；（2）文獻主要集中在少數具影響力之期刊；（3）大部分的文獻不被各種新聞與社群媒體所提及，主要被正式引用與被Mendeley讀者蒐藏；（4）高AAS的文獻主要被新聞、部落格，或是推特等來源所高度提及；（5）Altmetric.com的綜合指標AAS與推特、專利呈較高的相關性；（6）文獻被引用次數與推特推文提及之間的關係極弱；（7）Mendeley讀者數與文獻被引用次數之間的關係較強；（8）Mendeley讀者數與文獻在引文索引資料庫的使用次數關係緊密；（9）新聞提及指標與部落格提及指標關係緊密。本研究亦根據研究結果提出有關研究對象、研究方法與技術，以及未來研究方向的建議。 Informetrics and citation analysis are the main methods for evaluating research outputs in quantitative research assessment. There are various types of citation indicators, including Journal Impact Factor (JIF) in journal-level, number of citations in article-level, and h-index in author-level. On the background of Web 2.0 and Open Access (OA), as blogs and social networking sites have been common fields of academic exchange, scholarly communication is no longer confined to the past. In the context of the web and social media, traditional methods cannot assess scientific outputs comprehensively. Therefore, altmetrics, a novel concept that emerged in 2010, means that the study and use of scholarly impact measures based on online tools and environments for online activities.\nThis study aimed to compare and analyze citation indicators and altmetrics indicators, and investigating the relationship between the two indicators. This research analyzed the scientific outputs of 50 Nobel Prize Laureates in Physiology or Medicine in the 21st Century (2001-2020). 30 indicators were used in the study, including article-level and journal-level citation indicators, altmetrics indicators which acquired through Altmetric.com and Plum Analytics, Usage Count on Web of Science platform, and Mendeley readers. Correlation analysis, principal component analysis (PCA), and cluster analysis were used for statistical analysis.\nThe results of this study summarized as follows. (1) Three types of article-level citation indicators, - namely citation counts in Web of Science, Scopus, and Dimensions - are similar to each other. (2) Most of the articles were published in few prestigious journals such as Proceedings of the National Academy of Sciences of the United States of America, Nature, Science, and Cell. (3) Most articles are not mentioned by mainstream media and social media. (4) Papers with the higher Altmetric Attention Score (AAS) are highly mentioned by the news, blogs, and tweets. (5) AAS is highly correlated with patent citations and tweets. (6) There is a negligible relationship between citation and tweets. (7) Mendeley readers have a highly correlation with citations. (8) The correlations show a strong relationship between Mendeley readers and Usage Count on Web of Science platform. (9) News is closely connected to blogs. As regards research subjects, research methods and techniques, and future directions, suggestions are also proposed in this research. |
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Author cocitation: A literature measure of intellectual structure. Journal of the American Society for information Science, 32(3), 163-171.\nWouters, P., Zahedi, Z., & Costas, R. (2019). Social Media Metrics for New Research Evaluation, In W. Glänzel, H. F. Moed, U. Schmoch, & M. Thelwall (Eds), Springer Handbook of Science and Technology Indicators (pp. 687-713). Springer International Publishing. https://doi.org/10.1007/978-3-030-02511-3\nYang, S., Xing, X., & Wolfram, D. (2018). Difference in the impact of open-access papers published by China and the USA. Scientometrics, 115(2), 1017-1037. https://doi.org/10.1007/s11192-018-2697-7\nZhang, L., & Wang, J. (2018). Why highly cited articles are not highly tweeted? A biology case. Scientometrics, 117(1), 495-509. https://doi.org/10.1007/s11192-018-2876-6 | 描述: | 碩士 國立政治大學 圖書資訊與檔案學研究所 108155011 |
資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0108155011 | 資料類型: | thesis |
| Appears in Collections: | 學位論文 |
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| 501101.pdf | 1.98 MB | Adobe PDF2 | View/Open |
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