کاربرد نقش‌ها، تکامل ساختار فکری، و شبکه موضوعی هم‌رخدادی واژگان: حوزه طبقه‌بندی-ها و هستان‌شناسی‌های نقش مشارکت‌کنندگان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه علم اطلاعات و دانش‌شناسی، دانشکده علوم تربیتی و روان‌شناسی، دانشگاه الزهرا (س)، تهران، ایران،

2 استادیار، گروه پزشکی پیشگیری، دانشکده پزشکی فینبرگ، دانشگاه نورث وسترن، شیکاگو، آمریکا.

3 دانشجوی دکتری علم اطلاعات و دانش‌شناسی، گرایش مدیریت اطلاعات و دانش، دانشکده علوم تربیتی و روان‌شناسی، دانشگاه الزهرا (س)، تهران، ایران.

چکیده

هدف: هدف این پژوهش، تحلیل روند تکامل ساختار فکری، بررسی بلوغ خوشه­های موضوعی و تحلیل شبکه هم­رخدادی واژگان در حوزه طبقه‌بندی­ها و هستان‌شناسی­های نقش مشارکت‌کنندگان در پایگاه وب‌آوساینس با تأکید بر نقش­های «کردیت» به‌منظور ارتقای شفافیت و مسئولیت‌پذیری در مقالات علمی است.
روش‌شناسی: این پژوهش ازنظر هدف، کاربردی است و در دو بخش انجام‌شده است: بخش نخست با روش هم­رخدادی واژگان و رویکرد علم­سنجی و بخش دوم با روش مطالعات کتابخانه­ای و رویکرد توصیفی. جامعة پژوهش شامل تمامی کلیدواژه‌های استخراج‌شده از اسنادی است که طی سال‌های 1985 تا 2024 به زبان انگلیسی در پایگاه وب‌آوساینس نمایه شده‌اند. برای ترسیم و تحلیل شبکه­ها از نرم­افزارهای «ووس ویور» و بیبلیوشاینی استفاده‌شده است.
یافته‌ها: تحلیل هم‌واژگانی منجر به شکل‌گیری شش خوشه موضوعی شد. مصورسازی لایه­ای نشان داد که در بازة زمانی 2014 تا 2020، اهمیت کلیدواژه­ها در این حوزه بیشتر نمایان بوده است.
نتیجه‌گیری: نتایج پژوهش نشان داد که واژگان «انتساب نویسندگی» و «یادگیری ماشین» در شبکه هم­رخدادی، بالاترین میزان چگالی را نسبت به سایر گره­های شبکه دارند. بهره­گیری از کردیت، موجب تقویت یکپارچگی و اعتبار علمی پژوهش‌ها می­شود و امکان ارزیابی دقیق‌تری از نقش مشارکت‌های پژوهشگران را فراهم می‌سازد. همچنین، رؤیت‌پذیری فرد در مسیر حرفه­ای­ را برای توسعه فرصت­های شغلی بیشتر کرده و از سوء رفتارهای پژوهشی مانند سایه نویسی جلوگیری می­کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Role Use, Intellectual Structure Evolu-tion, and the Co-occurrence Topic Net-work of Vocabulary: The Domain of Role Classifications and Ontologies of Participants

نویسندگان [English]

  • Elaheh Hosseini 1
  • Mohammad Hosseini 2
  • Maral Alipour-Tehrani 3
1 Assistant Professor, Department of Information Science, Faculty of Education and Psychology, Alzahra University, Tehran, Iran
2 Assistant Professor, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
3 Ph.D. Student of Information Science and Knowledge Studies, Department of Information Science, Faculty of Education and Psychology, Alzahra University, Tehran, Iran
چکیده [English]

Purpose: Contributor Role Taxonomy (CRediT) offers a standardized set of 14 roles—including conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing (original draft), writing (review and editing), visualization, supervision, project administration, and funding acquisition—to specify contributions to scholarly publications. This study aimed to analyze the evolution of the intellectual structure, the maturity of thematic clusters, and the co-occurrence network of words related to contributor role ontologies and taxonomies within the Web of Science (WoS) database. The co-occurrence network of keywords and thematic clusters in the WoS database was visualized and analyzed to highlight thematic clusters in this context. Moreover, the study aimed to analyze the maturity of thematic clusters through a topic map and examine their evolution using a Sankey diagram.
Methodology: This study employed a literature review with a descriptive approach to provide a conceptual analysis of scholarly authorship and CRediT. This study utilized the co-occurrence word analysis technique, combined with a scientometric approach, was utilized. VOSviewer software, which applies smart local moving algorithms to identify topic clusters, was used for network mapping and analysis. The co-word analysis method was used to identify thematic clusters related to contributor role ontology and taxonomy and to map co-occurrence networks. The research included all keywords extracted from documents indexed in English in the Web of Science (WoS) database from 1985 to 2024. A database search using prominent words and phrases retrieved 2,126 documents. Additionally, R and BiblioShiny (the web-based interface of the Bibliometrix library) were utilized to generate visual maps. The strategic diagram (topic map) and Sankey diagram (topic evolution) were used to assess the maturity and development of the clusters.
Findings: Keyword clustering in the WoS database resulted in six distinct clusters: ‘bibliometric analysis in research authorship,’ ‘natural language processing and deep learning in authorship attribution,’ ‘authorship identification techniques via stylometry,’ ‘linguistic approaches to contributor role ontology,’ ‘data mining techniques for authorship role analysis,’ and ‘machine learning techniques for author attribution.’ The timeline overlay visualization of the WoS network revealed that between 2014 and 2020, the significance of keywords in this field increased notably. Additionally, 2020 held greater weight and importance within the network, encompassing the most relevant and prominent keywords, which highlights that the discourse surrounding contributor role ontologies and taxonomies has matured. The density visualization indicated that the terms ‘authorship attribution’ and ‘machine learning’ exhibited the highest density in this network, suggesting that machine learning techniques are widely employed to identify authorship and contributions. Various machine learning methods, data mining, deep learning, natural language processing, and linguistic approaches are utilized to evaluate research contributions. The findings from the Sankey diagram showed that between 2019 and 2024, four themes— ‘authorship,’ ‘attribution of authorship,’ ‘history,’ and ‘ontology of the contributory role’—persist. This continuity in related subjects implies that these concepts remain equally important in ongoing debates, with researchers conducting deeper and more advanced investigations in these areas.
Conclusion: Utilizing CRediT and adhering to ethical principles such as transparency, honesty, and integrity enhances the evaluation of researchers' contributions to scholarly work. It also increases individuals’ visibility in professional environments and supports researchers when applying for job opportunities. The results of this study indicate that, when seeking to improve recognition of scholarly contributions, the research community should look beyond traditional authorship issues and focus on developing a collaborative approach that preserves the rights and responsibilities of all contributors. Clearly describing the roles and contributions of both author and non-author contributors promotes ethical collaboration and encourages interdisciplinary partnerships. Although CRediT was initially developed for the health and biological sciences, it has since been adopted in other fields as well. This expansion highlights a growing interest across scholarly domains in improving recognition of contributions, which necessitates a closer examination of the tasks involved in various domains. Conducting quantitative and qualitative studies to determine which roles are most prominent in different fields would be a valuable direction for future research. Finally, our results emphasize the need to localize and integrate existing tools or develop context-specific solutions to enhance Iranian scholarly journals' management of information about scholarly contributions. This would enable researchers to register the roles and contributions of collaborators more quickly and easily when submitting manuscripts. Therefore, we suggest that administrators and digital developers of scholarly journals consider incorporating either the English version of CRediT roles or their translated equivalents into their infrastructure. In this regard, the results of this study can be seen as useful recommendations for the Publications Commission of the Iranian Ministry of Science, Research, and Technology, as well as the Ministry of Health and Medical Education. Developing policies and directives for editors of scholarly journals—published in both Persian and English—and mandating the use of contributor roles will facilitate the documentation of individual contributions during the submission process.

کلیدواژه‌ها [English]

  • Contributor role ontology
  • Contributor role taxonomy
  • CRediT
  • Intellectual structure of knowledge
  • Co-word analysis
  • Thematic clusters
احمدی، ح.، و عصاره، ف. (1396). مروری بر کارکردهای هم­واژگانی. مطالعات کتابداری و سازماندهی اطلاعات، 28(1)، 125-145. http://noo.rs/xhnE8
اکابری، آ.، و ضمیری‌نژاد، س. (1396). چگونه مسئله‌های مربوط به درج نام نویسندگان را حل‌وفصل کنیم؟ راهنمای پژوهشگران تازه‌کار. مجله دانشگاه علوم پزشکی سبزوار، 24(3)، 191-195.
حاجیان، ح.، و زرجینی، الف. (1402). تحلیلی بر کاربردهای داده‌کاوی در صنعت بیمه بر اساس شبکه هم‌رخدادی واژگان‌ها و شناسایی معتبرترین مجلات با شاخص استناد به پژوهش‌های علمی با استفاده از رویکرد علم‌سنجی. پژوهشنامه بیمه،  13(1)، 71-86. https://doi.org/10.22056/ijir.2024.01.06
رضائیان، م. (1388). چگونه می‌توان از جر و بحث نویسندگی پیشگیری نمود. مجله علمی دانشگاه علوم پزشکی رفسنجان، ۸(۲)، 75- 78.  http://journal.rums.ac.ir/article-1-587-fa.html
عباسی، ح.، حسینی‌نیا، غ.، و داوری، ع. (1400). نگاشت مفهومی رفتار کارآفرینانه کارکنان در سازمان‌های دولتی (رویکرد علم‌سنجی). پژوهشنامه مدیریت اجرایی، 13(26)، 193-220.
عصاره، ف.، سهیلی، ف.، و منصوری، ع. (۱۳۹3). علم‌سنجی و دیداری سازی اطلاعات. دانشگاه اصفهان.
کاظمیان، س. و.، و خادم رضاییان، م. (1401). مروری بر الگوهای نگارش مشارکت نویسندگان در مقالات پژوهشی و ارائه الگوی کاربردی: طیف رنگی مشارکت. مجله ایرانی آموزش در علوم پزشکی، 22(۲۸)، ۲۰۸-۲۲۲.
محمدی، س.، و آرازی، ت. (1393). اخلاق و عدالت در تعیین نام نویسندگان مقاله‌های علمی. اخلاق و تاریخ پزشکی ایران، 7(5)، 50-60. https://ijme.tums.ac.ir/article-1-5465-fa.html
مکی‌ زاده، ف.، حاضری، ا.، حسینی نسب، س. ح.، و سهیلی، ف. (1395). تحلیل موضوعی و ترسیم نقشه علمی مقالات مرتبط با حوزه درمان افسردگی در پابمد. مدیریت سلامت، 19(65)، 51-63.
Abbasi, H., Hosseininia, G. H., & Davari, A. (2021). Conceptual mapping of employees’ entrepreneurial behavior in government organizations using a scientometric approach. Journal of Executive Management13(26), 193-220.
Ahmadi, H., & Osareh, F. (2017). Co-word analysis concept, definition, and application. Librarianship and Information Organization Studies (Journal of National Studies on Librarianship and Information Organization), 28(1), 125-145. http://noo.rs/xhnE8
[In Persian].
Akaberi, A., & Zamirnejhad, S. (2017). How to handle authorship disputes. Journal of Sabzevar University of Medical Sciences, 24(3), 191-195.
Allen, L., O’Connell, A., & Kiermer, V. (2019). How can we ensure visibility and diversity in research contributions? how the contributor role taxonomy (CRediT) is helping the shift from authorship to contributorship. Learned Publishing, 32(1), 71-74.
Allen, L., Scott, J., Brand, A., Hlava, M., & Altman, M. (2014). Publishing: Credit where credit is due. Nature, 508(7496), 312-313. https://doi.org/10.1038/508312a
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Bhargava, M., Mehndiratta, P., & Asawa, K. (2013). Stylometric analysis for authorship attribution on Twitter. In V. Bhatnagar, & S. Srinivasa (Eds.), Big Data Analytics (Lecture Notes in Computer Science) (Vol. 8302, pp. 22–32). Springer.
Bird, S. J., Hosseini, M., & Plemmons, D. (2023). Authors Without Borders: Guidelines for Discussing Authorship with Collaborators. Sigma Xi, The Scientific Research Honor Society, Incorporated.       
Boyer, S., Ikeda, T., Lefort, M. C., Malumbres-Olarte, J., & Schmidt, J. M. (2017). Percentage-based Author Contribution Index: a universal measure of author contribution to scientific articles. Research Integrity and Peer Review2(1), 1-8.
Brand, A., Allen, L., Altman, M., Hlava, M., & Scott, J. (2015). Beyond authorship: Attribution, contribution, collaboration, and credit. Learned Publishing, 28(2), 151–155.
Brusco, M., Steinley, D., & Watts, A. L. (2022). A comparison of spectral clustering and the walktrap algorithm for community detection in network psychometrics. Psychological Methods, 29(4), 704-722. https://doi.org/10.1037/met0000509
Callon, M., Courtial, J. P., & Turner, W. (1986). Future developments. In M. Callon, J. Law, & A. Rip (Eds.), Mapping The Dynamics Of Science And Technology (pp. 211-217). Palgrave Macmillan. https://doi.org/10.1007/978-1-349-07408-2_12
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A Practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146-166.
Craig, C. (2018). Contributorship and authorship hierarchy as a form of credit. In P. A. Mabrouk, & J. N. Currano, Credit Where Credit Is Due: Respecting Authorship and Intellectual Property (pp. 37-49). American Chemical Society.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Hajiyan, H., & Zarjini, A. (2023). A comprehensive analysis of the keywords co-occurrence network and the most cited journals on data mining techniques in the insurance industry using scientometrics approach. Iranian Journal of Insurance Research13(1), 71-86.
He, X., Lashkari, A. H., Vombatkere, N., & Sharma, D. P. (2024). Authorship Attribution Methods, Challenges, and Future Research Directions: A Comprehensive Survey. Information15(3), 131. https://doi.org/10.3390/info15030131
Helgesson, G., & Eriksson, S. (2018). Authorship order. Learned Publishing32(2), 106-112. https://doi.org/10.1002/leap.1191
Hoekman, J., & Rake, B. (2024). Geography of authorship: How geography shapes authorship attribution in big team science. Research Policy53(2), 104927.
Holcombe A. O., Kovacs, M., Aust, F., & Aczel, B. (2020). Documenting contributions to scholarly articles using CRediT and tensing. PLOS ONE, 15(12), e0244611.       https://doi.org/10.1371/journal.pone.0244611
Holcombe, A. O. (2019-a). Farewell, authors; hello contributors. Nature, 571(7763), 147.
Holcombe, A. O. (2019-b). Contributorship, not authorship: Use CRediT to indicate who did what. Publications, 7(3), 48. https://doi.org/10.3390/publications7030048
Hosseini, M., & Gordijn, B. (2020). A review of the literature on ethical issues related to scientific authorship. Accountability in Research, 27(5), 284-324.
Hosseini, M., Colomb, J., Holcombe, A. O., Kern, B., Vasilevsky, N. A., & Holmes, K. L. (2022-a). Evolution and adoption of contributor role ontologies and taxonomies. Learned Publishing36(2), 275-284. https://doi.org/10.1002/leap.1496
Hosseini, M., Gordijn, B., Wafford, Q. E., & Holmes, K. L. (2023). A systematic scoping review of the ethics of contributor role ontologies and taxonomies. Accountability in Research, 31(6), 678–705. https://doi.org/10.1080/08989621.2022.2161049
Hosseini, M., Lewis, J., Zwart, H., & Gordijn, B. (2022-b). An ethical exploration of increased average number of authors per publication. Science and Engineering Ethics, 28(3), 25. https://doi.org/10.1007/s11948-021-00352-3
Hu, C. P., Hu, J. M., Deng, S. L., & Liu, Y. (2013). A co-word analysis of library and information science in China. Scientometrics97(2), 369-382.
Hwang, S. S., Song, H. H., Baik, J. H., Jung, S. L., Park, S. H., Choi, K. H., & Park, Y. H. (2003). Researcher contributions and fulfillment of ICMJE authorship criteria: analysis of author contribution lists in research articles with multiple authors published in Radiology. Radiology226(1), 16-23.  https://doi.org/10.1148/radiol.2261011255
Ilik, V., Conlon, M., Triggs, G., White, M., Javed, M., Brush, M., Gutzman, K., Essaid, S., Friedman, P., Porter, S., Szomszor, M., Haendel, M. A., Eichmann, D., & Holmes, K. L. (2018). OpenVIVO: transparency in scholarship. Frontiers in Research Metrics and Analytics, 2(12), 1-11. https://doi.org/10.3389/frma.2017.00012
IWCSA Report. (2012).  Report on the International Workshop on Contributorship and Scholarly Attribution, May 16. Harvard University and Wellcome Trust.
Jockers, M. L., & Witten, D. M. (2010). A comparative study of machine learning methods for authorship attribution. Literary and Linguistic Computing25(2), 215-223.
Kazemian, S. V., & Khadem-Rezaiyan, M. (2022). A review of writing patterns of authors' participation in research articles and presenting a practical pattern: Color-coded contributions. Iranian Journal of Medical Education, 22(28), 208-222.
Khasseh, A. A., Soheili, F., Sharif Moghaddam, H., & Mousavi Chelak, A. (2017). Intellectual structure of knowledge in iMetrics: A co-word analysis. Information Processing & Management, 53(3), 705-720. https://doi.org/10.1016/j.ipm.2017.02.001
King, J. (1987). A review of bibliometric and other science indicators and their role in research evaluation. Journal of Information Science, 13(5), 261-276.
Koppel, M., Schler, J., & Argamon, S. (2009). Computational methods in authorship attribution. Journal of the American Society for Information Science and Technology60(1), 9-26. https://doi.org/10.1002/asi.20961
Larivière, V., Pontille, D., & Sugimoto, C. R. (2021). Investigating the division of scientific labor using the Contributor Roles Taxonomy (CRediT). Quantitative Science Studies, 2(1), 111-128. https://doi.org/10.1162/qss_a_00097
Lee, W. H. (2008). How to identify emerging research fields using scientometrics: An example in the field of information security. Scientometrics, 76(3), 503–525.
Maditati, D. R., Munim, Z. H., Schramm, H. J., & Kummer, S. (2018). A review of green supply chain management: From bibliometric analysis to a conceptual framework and future research directions. Resources, Conservation and Recycling139, 150-162.
Makkizadeh, F., Hazeri, A., Hosaininasab, S. H., & Soheili, F. (2016). Thematic analysis and scientific mapping of papers related to depression therapy in PubMed. Health Management, 19(65), 51–63. https://jha.iums.ac.ir/article-1-2074-en.html [In Persian].
Matarese, V., & Shashok, K. (2019). Transparent attribution of contributions to research: aligning guidelines to real-life practices. Publications7(2), 24.
McLaren, C., & Dent, A. (2021). Quantifying the contributions technicians make to research. Research Evaluation30(1), 51-56. https://doi.org/10.1093/reseval/rvaa035
McNutt, M. K., Bradford, M., Drazen, J. M., Hanson, B., Howard, B., Jamieson, K. H., Kiermer, V., Marcus, E., Pope, B. K., Schekman, R., Swaminathan, S., Stang, P. J., & Verma, I. M. (2018). Transparency in authors' contributions and responsibilities to promote integrity in scientific publication. Proceedings of the National Academy of Sciences of the United States of America, 115(11), 2557–2560. https://doi.org/10.1073/pnas.1715374115
Mohammadi, S., & Arazi, T. (2015). Ethical considerations in naming authors of scientific papers. IJMEHM, 7(5), 50-60. https://ijme.tums.ac.ir/article-1-5465-en.html [In Persian].
NISO. (2022). CRediT, Contributor Roles Taxonomy (ANSI/NISO Z39.104-2022). National Information Standards Organization (NISO). https://doi.org/10.3789/ansi.niso.z39.104-2022
Osareh, F., Soheili, F., & Mansouri, A. (2015). Scientometrics and Information Visualization. University of Isfahan. https://press.ui.ac.ir/book_300.html [In Persian].
Otto, E., Culakova, E., Meng, S., Zhang, Z., Xu, H., Mohile, S., & Flannery, M. A. (2022). Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer. Journal of geriatric oncology13(5), 742-746.
Ramezani, R. (2021). A language-independent authorship attribution approach for author identification of text documents. Expert Systems with Applications180, 115139.
Ramnial, H., Panchoo, S., & Pudaruth, S. (2016). Authorship attribution using stylometry and machine learning techniques [Conference Presentation]. Intelligent Systems Technologies and Applications (Vol. 1, pp. 113-125). Springer International Publishing.
Rennie, D., Yank, V., & Emanuel, L. (1997). When authorship fails: a proposal to make contributors accountable. JAMA278(7), 579-585.
Rezaeian, M. (2009). How to prevent authorship dispute. Journal of Rafsanjan University of Medical Sciences, 8(2), 75-78. http://journal.rums.ac.ir/article-1-587-en.html [In Persian].
Savoy, J. (2012). Authorship attribution: A comparative study of three text corpora and three languages. Journal of Quantitative Linguistics19(2), 132-161.
Smith, E., Williams-Jones, B., Master, Z., Larivière, V., Sugimoto, C. R., Paul-Hus, A., Shi, M., Diller, E., Caudle, K., & Resnik, D. B. (2019). Researchers' perceptions of ethical authorship distribution in collaborative research teams. Science and Engineering Ethics, 26(4), 1995–2022. https://doi.org/10.1007/s11948-019-00113-3
Stańczyk, U., & Cyran, K. A. (2007). Machine learning approach to authorship attribution of literary texts. International Journal of Applied Mathematics and Informatics1(4), 151-158. http://www.naun.org/main/UPress/ami/ami-22.pdf
Uchendu, A., Le, T., & Lee, D. (2023). Attribution and obfuscation of neural text authorship: A data mining perspective. ACM SIGKDD Explorations Newsletter25(1), 1-18.
Van Eck, N. J., & Waltman, L. (2018). VOSviewer Manual. Universiteit Leiden; CWTS. http://www.vosviewer.com/download/f-z2w2.Pdf.
Vasilevsky, N. A., Hosseini, M., Teplitzky, S., Ilik, V., Mohammadi, E., Schneider, J., Kern, B., Colomb, J., Edmunds, S. C., Gutzman, K., Himmelstein, D. S., White, M., Smith, B., O'Keefe, L., Haendel, M., & Holmes, K. L. (2021). Is authorship sufficient for today's collaborative research? A call for contributor roles. Accountability in Research, 28(1), 23–43. https://doi.org/10.1080/08989621.2020.1779591
Whittaker, J. (1989). Creativity and Conformity in Science: Titles, Keywords, and Co-word Analysis. Social Studies of Science, 19(3), 473-496.
Zheng, W., & Jin, M. (2023). A review on authorship attribution in text mining. Wiley Interdisciplinary Reviews: Computational Statistics15(2), e1584.
Zietman, A. L. (2017). The Ethics of Scientific Publishing: Black, White, and “Fifty Shades of Gray.” International Journal of Radiation Oncology Biology Physics, 99(2), 275–279.