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Title:	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
Authors:	董冠麟 Tung, Kuan-Lin
Contributors:	蔡明月 Tsay, Ming-Yueh 董冠麟 Tung, Kuan-Lin
Keywords:	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
Date:	2021
Issue Date:	2021-09-02 16:35:16 (UTC+8)
Abstract:	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。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. This 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. The 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.
Reference:	一、中文部分毛慶禎（2007）。開放進用運動的真諦。臺灣圖書館管理季刊，3(2)，1-14。王崇德（1980）。計量文獻與預測情報。情報科學，3，43-45。何光國（1994）。文獻計量學導論。臺北市：三民書局。余厚強、別克扎提．木拉提（2020）。從ISSI 2019會議解讀替代計量學研究新進展。情報理論與實踐，43(7)，157-164。彭辛茹（2020年5月22日）。喝碳酸飲料會加速老化速度！日飲500毫升就減少腦細胞4.6年壽命。Heho健康。https://heho.com.tw/archives/83284 黃元鶴（2019）。社會企業文獻計量統合分析與替代計量探索研究。圖資與檔案學刊，11(2)，37-77。http://doi.org/10.6575/JILA.201912_(95).0002 黃俊英（2000）。多變量分析（第七版）。臺北市：中國經濟企業研究所。楊思洛、王雨、祁凡（2020）。系統視角下Altmetrics的發展趨勢：融合、開放、深化。情報理論與實踐，43(4)，32-39。蔡明月（2002）。網路計量學。圖書與資訊學刊，42，1-14。蔡明月（2003）。資訊計量學與文獻特性。臺北：華泰。蔡明月、曾苓莉（2014）。網路計量學新指標Altmetrics。教育資料與圖書館學，51，91-120。https://doi.org/DOI:10.6120/JoEMLS.2014.51S/0655.OR.AM 蕭文龍（2020）。統計分析入門與應用：SPSS中文版+SmartPLS 3(PLS-SEM)（第三版）。臺北市：碁峰資訊。二、英文部分 Almind, T. C., & Ingwersen, P. (1997). Informetric analyses on the World Wide Web: Methodological approaches to `webometrics`. Journal of Documentation, 53(4), 404-426. https://doi.org/10.1108/EUM0000000007205 Altmetric (n.d.a). About us. https://www.altmetric.com/about-us/ Altmetric (n.d.b). Sources of Attention. https://www.altmetric.com/about-our-data/our-sources/ Altmetric (n.d.c). How it works. https://www.altmetric.com/about-our-data/how-it-works/ Altmetric Solutions (2020). How is the Altmetric Attention Score calculated? https://help.altmetric.com/support/solutions/articles/6000233311-how-is-the-altmetric-attention-score-calculated- Association of College & Research Libraries (2003). Scholarly Communication Toolkit: Scholarly Communication Overview. https://acrl.libguides.com/scholcomm/toolkit Azer, S. A., & Azer, S. (2019). Top-cited articles in medical professionalism: a bibliometric analysis versus altmetric scores. BMJ Open, 9(7), e029433. https://doi.org/10.1136/bmjopen-2019-029433 Baas, J., Schotten, M., Plume, A., Côté, G., & Karimi, R. (2020). Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, 1(1), 377–386. https://doi.org/10.1162/qss_a_00019 Barakat, A. F., Nimri, N., Shokr, M., Mahtta, D., Mansoor, H., Masri, A., & Elgendy, I. Y. (2019). Correlation of altmetric attention score and citations for high-impact general medicine journals: a cross-sectional study. Journal of General Internal Medicine, 34(6), 825-827. https://doi.org/10.1007/s11606-019-04838-6 Bardus, M., El Rassi, R., Chahrour, M., Akl, E. W., Raslan, A. S., Meho, L. I., & Akl, E. A. (2020). The use of social media to increase the impact of health research: systematic review. Journal of Medical Internet Research, 22(7), e15607. https://doi.org/10.2196/15607 Birkle, C., Pendlebury, D. A., Schnell, J., & Adams, J. (2020). Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies, 1(1), 363–376. https://doi.org/10.1162/%20qss_a_00018 Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216-1227. https://doi.org/10.1002/asi.20077 Bornmann, L. (2014). Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics. Journal of Informetrics, 8(4), 895-903. https://doi.org/10.1016/j.joi.2014.09.005 Bornmann, L. (2015). Alternative metrics in scientometrics: A meta-analysis of research into three altmetrics. Scientometrics, 103(3), 1123-1144. https://doi.org/10.1007/s11192-015-1565-y Bornmann, L. (2016). What do altmetrics counts mean? A plea for content analyses. Journal of the Association for Information Science and Technology, 67(4), 1016-1017. https://doi.org/10.1002/asi.23633 Budapest Open Access Initiative (2002). Read the Budapest Open Access Initiative. https://www.budapestopenaccessinitiative.org/read Cell (n.d.). Aims and scope. https://www.cell.com/cell/aims Chang, J., Desai, N., & Gosain, A. (2019). Correlation between altmetric score and citations in pediatric surgery core journals. Journal of Surgical Research, 243, 52-58. https://doi.org/10.1016/j.jss.2019.05.010 Chi, P. S., & Glänzel, W. (2017). An empirical investigation of the associations among usage, scientific collaboration and citation impact. Scientometrics, 112(1), 403-412. https://doi.org/10.1007/s11192-017-2356-4 Chi, P. S., Gorraiz, J., & Glänzel, W. (2019). Comparing capture, usage and citation indicators: an altmetric analysis of journal papers in chemistry disciplines. Scientometrics, 120(3), 1461-1473. https://doi.org/10.1007/s11192-019-03168-y Clarivate (n.d.). Web of Science: Science Citation Index Expanded. https://clarivate.com/webofsciencegroup/solutions/webofscience-scie/ Clarivate Web of Science Group (n.d.). World’s largest publisher-neutral citation index and research intelligence platform. https://clarivate.com/webofsciencegroup Clement, J. (2020, May 18). Social media - Statistics & Facts. https://www.statista.com/topics/1164/social-networks/ Costas, R., Zahedi, Z., & Wouters, P. (2015a). Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the Association for Information Science and Technology, 66(10), 2003-2019. https://doi.org/10.1002/asi.23309 Costas, R., Zahedi, Z., & Wouters, P. (2015b). The thematic orientation of publications mentioned on social media: Large-scale disciplinary comparison of social media metrics with citations. Aslib Journal of Information Management, 67(3), 260-288. https://doi.org/10.1108/AJIM-12-2014-0173 CWTS Leiden Ranking (2020). Indicators. https://www.leidenranking.com/information/indicators de Winter, J. C. (2015). The relationship between tweets, citations, and article views for PLOS ONE articles. Scientometrics, 102(2), 1773-1779. https://doi.org/10.1007/s11192-014-1445-x Delli, K., Livas, C., Spijkervet, F. K. L., & Vissink, A. (2017). Measuring the social impact of dental research: An insight into the most influential articles on the Web. Oral Diseases, 23(8), 1155-1161. https://doi.org/10.1111/odi.12714 Directory of Open Access Journals (n.d.). Find open access journals & articles. https://doaj.org/ Drongstrup, D., Malik, S., Aljohani, N. R., Alelyani, S., Safder, I., & Hassan, S. U. (2020). Can social media usage of scientific literature predict journal indices of AJG, SNIP and JCR? An altmetric study of economics. Scientometrics, 125(2), 1541-1558. https://doi.org/10.1007/s11192-020-03613-3 Ebrahimy, S., Mehrad, J., Setareh, F., & Hosseinchari, M. (2016). Path analysis of the relationship between visibility and citation: the mediating roles of save, discussion, and recommendation metrics. Scientometrics, 109(3), 1497-1510. https://doi.org/10.1007/s11192-016-2130-z Egghe, L. & Rousseau, R. (1990). Introduction to Informetrics: Quantitative Methods in Library, Documentation and Information Science. Elsevier. Elsevier (n.d.). About Scopus – Abstract and citation database. https://www.elsevier.com/solutions/scopus Erdt, M., Nagarajan, A., Sin, S. C. J., & Theng, Y. L. (2016). Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media. Scientometrics, 109(2), 1117-1166. https://doi.org/10.1007/s11192-016-2077-0 Fenner, M. (2013). What Can Article-Level Metrics Do for You? PLOS Biology, 11(10), e1001687. https://doi.org/10.1371/journal.pbio.1001687 Garcovich, D., Ausina Marquez, V., & Adobes Martin, M. (2020). The online attention to research in periodontology: An Altmetric study on the most discussed articles on the web. Journal of Clinical Periodontology, 47(3), 330-342. https://doi.org/10.1111/jcpe.13221 Giustini, A. J., Axelrod, D. M., Lucas, B. P., & Schroeder, A. R. (2020). Association between citations, altmetrics, and article views in pediatric research. JAMA Network Open, 3(7), e2010784. https://doi.org/10.1001/jamanetworkopen.2020.10784 Haustein, S. (2016). Grand challenges in altmetrics: heterogeneity, data quality and dependencies. Scientometrics, 108(1), 413-423. https://doi.org/10.1007/s11192-016-1910-9 Haustein, S., Bowman, T. D., & Costas, R. (2016). Interpreting “altmetrics”: viewing acts on social media through the lens of citation and social theories. In C. R. Sugimoto (Ed.), Theories of Informetrics and Scholarly Communication (pp. 372-405). de Gruyter Mouton. https://doi.org/10.1515/9783110308464 Haustein, S., Costas, R., & Larivière, V. (2015). Characterizing social media metrics of scholarly papers: The effect of document properties and collaboration patterns. PLOS ONE, 10(3), e0120495. https://doi.org/10.1371/journal.pone.0120495 Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M., & Larivière, V. (2014). Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature. Journal of the Association for Information Science and Technology, 65(4), 656-669. https://doi.org/10.1002/asi.23101 Huang, W., Wang, P., & Wu, Q. (2018). A correlation comparison between Altmetric Attention Scores and citations for six PLOS journals. PLOS ONE, 13(4), e0194962. https://doi.org/10.1371/journal.pone.0194962 Jia, J. L., Nguyen, B., Mills, D. E., Polin, D. J., & Sarin, K. Y. (2020). Comparing Online Engagement and Academic Impact of Dermatology Research: An Altmetric Attention Score and PlumX Metrics Analysis. Journal of the American Academy of Dermatology, 83(2), 648-650. https://doi.org/10.1016/j.jaad.2019.12.003 Jolliffe, I. T. (2011). Principal Component Analysis. In L. Miodrag (Ed.), International Encyclopedia of Statistical Science. SpringerLink. https://doi.org/10.1007/978-3-642-04898-2 Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202 Journal of Biological Chemistry (n.d.). About JBC. https://www.jbc.org/content/about Journal of Virology (n.d.). About JVI. https://journals.asm.org/journal/jvi/about Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39, 31-36. Kampman, J. M., Hermanides, J., Boere, P. R., & Hollmann, M. W. (2020). Appreciation of literature by the anaesthetist: A comparison of citations, downloads and Altmetric Attention Score. Acta Anaesthesiologica Scandinavica, 64(6), 823-828. https://doi.org/10.1111/aas.13575 Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003 Kessler, M. M. (1963). Bibliographic coupling extended in time: Ten case histories. Information Storage and Retrieval, 1, 169–187. Kolahi, J., Khazaei, S., Iranmanesh, P., Khademi, A., Nekoofar, M. H., & Dummer, P. M. H. (2020). Altmetric analysis of the contemporary scientific literature in Endodontology. International Endodontic Journal, 53(3), 308-316. https://doi.org/10.1111/iej.13226 Livas, C., & Delli, K. (2018). Looking beyond traditional metrics in orthodontics: an altmetric study on the most discussed articles on the web. European Journal of Orthodontics, 40(2), 193-199. https://doi.org/10.1093/ejo/cjx050 McCain, K W. (1991). Mapping economics through the journal literature: An experiment in journal co-citation analysis. Journal of the American Society for Information Science, 42(4), 290-296. Meschede, C., & Siebenlist, T. (2018). Cross-metric compatability and inconsistencies of altmetrics. Scientometrics, 115(1), 283-297. https://doi.org/10.1007/s11192-018-2674-1 Moed, H. F. (2017). Applied Evaluative Informetrics. Springer International Publishing. https://doi.org/10.1007/978-3-319-60522-7 Moed, H. F., & Halevi, G. (2015). Multidimensional assessment of scholarly research impact. Journal of the Association for Information Science and Technology, 66(10), 1988-2002. https://doi.org/10.1002/asi.23314 Mohammadi, E., Thelwall, M., Haustein, S., & Larivière, V. (2015). Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the Association for Information Science and Technology, 66(9), 1832-1846. https://doi.org/10.1002/asi.23286 National Information Standards Organization (2014). Alternative Metrics Initiative Phase 1 White Paper. https://groups.niso.org/apps/group_public/download.php/13809/Altmetrics_projecP_Thase1_white_paper.pdf National Information Standards Organization (2016). Outputs of the NISO Alternative Assessment Metrics Project. https://groups.niso.org/apps/group_public/download.php/17091/ National Information Standards Organization (n.d.). NISO Alternative Assessment Metrics (Altmetrics) Initiative. https://www.niso.org/standards-committees/altmetrics Nature (n.d.). About the Journal. https://www.nature.com/nature/about Nocera, A. P., Boyd, C. J., Boudreau, H., Hakim, O., & Rais-Bahrami, S. (2019). Examining the correlation between Altmetric score and citations in the urology literature. Urology, 134, 45-50. https://doi.org/10.1016/j.urology.2019.09.014 Ortega, J. L. (2018). Disciplinary differences of the impact of altmetric. FEMS microbiology letters, 365(7), fny049. https://doi.org/10.1093/femsle/fny049 Ortega, J. L. (2020). Proposal of composed altmetric indicators based on prevalence and impact dimensions. Journal of Informetrics, 14(4), 101071. https://doi.org/10.1016/j.joi.2020.101071 Patel, R. B., Vaduganathan, M., Bhatt, D. L., & Bonow, R. O. (2018). Characterizing high-performing articles by Altmetric Score in major cardiovascular journals. JAMA Cardiology, 3(12), 1249-1251. https://doi.org/10.1001/jamacardio.2018.3823 Pinfield, S., Wakeling, S., Bawden, D., & Robinson, L. (2020). Open Access in Theory and Practice: The Theory-Practice Relationship and Openness. Routledge. https://doi.org/10.4324/9780429276842 Piwowar, H., Priem, J., Larivière, V., Alperin, J. P., Matthias, L., Norlander, B., ... & Haustein, S. (2018). The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles. PeerJ, 6, e4375. https://doi.org/10.7717/peerj.4375 PLOS (n.d.). Assessment of Impact with Article-Level Metrics (ALMs). https://plos.org/publish/metrics/ Plum Analytics (n.d.a). Leadership. https://plumanalytics.com/about/leadership/ Plum Analytics (n.d.b). About PlumX Metrics. https://plumanalytics.com/learn/about-metrics/ Priem, J., & Hemminger, B. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7). https://doi.org/10.5210/fm.v15i7.2874 Priem, J., Groth, P., & Taraborelli, D. (2012). The altmetrics collection. PloS ONE, 7(11), e48753. https://doi.org/10.1371/journal.pone.0048753 Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2010). Altmetrics: a manifesto. http://altmetrics.org/manifesto/ Pritchard, A. (1969). Statistical Bibliography or Bibliometrics? Journal of Documentation, 25(4), 348–349. Proceedings of the National Academy of Sciences of the United States of America (n.d.). About PNAS. https://www.pnas.org/page/about Punia, V., Aggarwal, V., Honomichl, R., & Rayi, A. (2019). Comparison of Attention for Neurological Research on Social Media vs Academia: An Altmetric Score Analysis. JAMA neurology, 76(9), 1122-1124. https://doi.org/10.1001/jamaneurol.2019.1791 Research. (n.d.). In Oxford English Dictionary. Retrieved January, 15, 2020, from https://www.lexico.com/definition/research Romesburg, H. C. (2011). Cluster Analysis: An Introduction. In L. Miodrag (Ed.), International Encyclopedia of Statistical Science. SpringerLink. https://doi.org/10.1007/978-3-642-04898-2 Rousseau, R., Egghe, L., & Guns, R. (2018). Becoming Metric-Wise: A Bibliometrics Guide for Researchers. Elsevier. https://doi.org/10.1016/C2017-0-01828-1 Scholarly Publishing and Academic Resources Coalition (n.d.). What are Article-Level Metrics? https://sparcopen.org/our-work/article-level-metrics/ Science (n.d.). About Science & AAAS. https://www.sciencemag.org/about/about-science-aaas Scopus (2019). Fact sheet. https://www.elsevier.com/__data/assets/pdf_file/0017/114533/Scopus_GlobalResearch_Factsheet2019_FINAL_WEB.pdf Shema, H., Bar‐Ilan, J., & Thelwall, M. (2014). Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics. Journal of the Association for Information Science and Technology, 65(5), 1018-1027. https://doi.org/10.1002/asi.23037 Small, H. G. (1973). Co-citation in the Scientific Literature: A Measure of the Relationship between Two Documents. Journal of the American Society for Information Science, 24, 265-269. Smith, L. C. (1981). Citation Analysis. Library Trend, 30(1), 83-106. Statistics Solutions (n.d.). Correlation (Pearson, Kendall, Spearman). https://www.statisticssolutions.com/correlation-pearson-kendall-spearman/ Sugimoto, C. R., Work, S., Larivière, V., & Haustein, S. (2017). Scholarly use of social media and altmetrics: A review of the literature. Journal of the Association for Information Science and Technology, 68(9), 2037-2062. https://doi.org/10.1002/asi.23833 Taylor, R. B. (2018). Medical Writing: A Guide for Clinicians, Educators, and Researchers (3rd ed.). Springer. https://doi.org/10.1007/978-3-319-70126-4 The Journal of Antibiotics (n.d.). About the Journal. https://www.nature.com/ja/about The Nobel Prize (n.d.). The Nobel Prize in Physiology or Medicine. https://www.nobelprize.org/prizes/medicine/ Thelwall, M. (2020). The Pros and Cons of the Use of Altmetrics in Research Assessment. Scholarly Assessment Reports, 2(1), 2. http://doi.org/10.29024/sar.10 Thelwall, M., & Kousha, K. (2015). Web Indicators for Research Evaluation. Part 2: Social Media Metrics. El profesional de la información, 24(5), 607-620. https://doi.org/10.3145/epi.2015.sep.09 Wang, Z., Glänzel, W., & Chen, Y. (2020). The impact of preprints in Library and Information Science: an analysis of citations, usage and social attention indicators. Scientometrics, 125, 1403-1423. https://doi.org/10.1007/s11192-020-03612-4 Warren, V. T., Patel, B., & Boyd, C. J. (2020). Analyzing the relationship between Altmetric score and literature citations in the Implantology literature. Clinical Implant Dentistry and Related Research, 22(1), 54-58. https://doi.org/10.1111/cid.12876 White, H. D., & Griffith, B. C. (1981). Author cocitation: A literature measure of intellectual structure. Journal of the American Society for information Science, 32(3), 163-171. Wouters, 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 Yang, 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 Zhang, 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
Description:	碩士國立政治大學圖書資訊與檔案學研究所 108155011
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0108155011
Data Type:	thesis
DOI:	10.6814/NCCU202101326
Appears in Collections:	[Graduate Institute of Library, Information and Archival Studies] Theses

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