IDEAS home Printed from https://ideas.repec.org/r/spr/scient/v102y2015i1d10.1007_s11192-014-1402-8.html
   My bibliography  Save this item

Mapping the intellectual structure of scientometrics: a co-word analysis of the journal Scientometrics (2005–2010)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. O. Mryglod & Yu. Holovatch & R. Kenna & B. Berche, 2016. "Quantifying the evolution of a scientific topic: reaction of the academic community to the Chornobyl disaster," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1151-1166, March.
  2. Yang, Chao & Huang, Cui & Su, Jun, 2018. "An improved SAO network-based method for technology trend analysis: A case study of graphene," Journal of Informetrics, Elsevier, vol. 12(1), pages 271-286.
  3. Carlos Olmeda-Gómez & Maria-Antonia Ovalle-Perandones & Antonio Perianes-Rodríguez, 2017. "Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 195-217, October.
  4. Qu Zhao, 2018. "Electromobility research in Germany and China: structural differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 473-493, October.
  5. Yu Song & Bingrui Liu & Xiaohong Chen & Jia Liu, 2020. "Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-Based Weighted Co-Word Analysis," IJERPH, MDPI, vol. 17(3), pages 1-16, January.
  6. Faraji, Omid & Ezadpour, Mostafa & Rahrovi Dastjerdi, Alireza & Dolatzarei, Ehsan, 2022. "Conceptual structure of balanced scorecard research: A co-word analysis," Evaluation and Program Planning, Elsevier, vol. 94(C).
  7. Emilio Abad-Segura & Francisco Joaquín Cortés-García & Luis J. Belmonte-Ureña, 2019. "The Sustainable Approach to Corporate Social Responsibility: A Global Analysis and Future Trends," Sustainability, MDPI, vol. 11(19), pages 1-24, September.
  8. Seyedmohammadreza Hosseini & Hamed Baziyad & Rasoul Norouzi & Sheida Jabbedari Khiabani & Győző Gidófalvi & Amir Albadvi & Abbas Alimohammadi & Seyedehsan Seyedabrishami, 2021. "Mapping the intellectual structure of GIS-T field (2008–2019): a dynamic co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2667-2688, April.
  9. Chin-Ling Lee & Robert Strong & Kim E. Dooley, 2021. "Analyzing Precision Agriculture Adoption across the Globe: A Systematic Review of Scholarship from 1999–2020," Sustainability, MDPI, vol. 13(18), pages 1-15, September.
  10. Wang, Chao & Lim, Ming K & Zhao, Longfeng & Tseng, Ming-Lang & Chien, Chen-Fu & Lev, Benjamin, 2020. "The evolution of Omega-The International Journal of Management Science over the past 40 years: A bibliometric overview," Omega, Elsevier, vol. 93(C).
  11. Manuel Castriotta & Michela Loi & Elona Marku & Ludovica Moi, 2021. "Disentangling the corporate entrepreneurship construct: conceptualizing through co-words," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2821-2863, April.
  12. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
  13. Manuel Castriotta & Maria Chiara Guardo, 2016. "Disentangling the automotive technology structure: a patent co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 819-837, May.
  14. Ferreira de Araújo Lima, Priscila & Crema, Maria & Verbano, Chiara, 2020. "Risk management in SMEs: A systematic literature review and future directions," European Management Journal, Elsevier, vol. 38(1), pages 78-94.
  15. Espécie, Mariana de Assis & de Carvalho, Pedro Ninô & Pinheiro, Maria Fernanda Bacile & Rosenthal, Vinicius Mesquita & da Silva, Leyla A. Ferreira & Pinheiro, Mariana Rodrigues de Carvalhaes & Espig, , 2019. "Ecosystem services and renewable power generation: A preliminary literature review," Renewable Energy, Elsevier, vol. 140(C), pages 39-51.
  16. Hai-Yun Xu & Zeng-Hui Yue & Chao Wang & Kun Dong & Hong-Shen Pang & Zhengbiao Han, 2017. "Multi-source data fusion study in scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 773-792, May.
  17. Marie Katsurai & Shunsuke Ono, 2019. "TrendNets: mapping emerging research trends from dynamic co-word networks via sparse representation," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1583-1598, December.
  18. Qikai Cheng & Jiamin Wang & Wei Lu & Yong Huang & Yi Bu, 2020. "Keyword-citation-keyword network: a new perspective of discipline knowledge structure analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1923-1943, September.
  19. Manuel Castriotta & Michela Loi & Elona Marku & Luca Naitana, 2019. "What’s in a name? Exploring the conceptual structure of emerging organizations," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 407-437, February.
  20. Shiyun Wang & Jin Mao & Yujie Cao & Gang Li, 2022. "Integrated knowledge content in an interdisciplinary field: identification, classification, and application," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6581-6614, November.
  21. Zhao Qu & Shanshan Zhang & Chunbo Zhang, 2017. "Patent research in the field of library and information science: Less useful or difficult to explore?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 205-217, April.
  22. Bei-Ni Yan & Tian-Shyug Lee & Tsung-Pei Lee, 2015. "Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1285-1300, November.
  23. Li, Xin & Xie, Qianqian & Daim, Tugrul & Huang, Lucheng, 2019. "Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 432-449.
  24. Christian Weismayer & Ilona Pezenka, 2017. "Identifying emerging research fields: a longitudinal latent semantic keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1757-1785, December.
  25. Rongying Zhao & Xinlai Li & Zhisen Liang & Danyang Li, 2019. "Development strategy and collaboration preference in S&T of enterprises based on funded papers: a case study of Google," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 323-347, October.
  26. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
  27. Zhang, Yi & Wu, Mengjia & Miao, Wen & Huang, Lu & Lu, Jie, 2021. "Bi-layer network analytics: A methodology for characterizing emerging general-purpose technologies," Journal of Informetrics, Elsevier, vol. 15(4).
  28. Aliakbar Pourhatami & Mohammad Kaviyani-Charati & Bahareh Kargar & Hamed Baziyad & Maryam Kargar & Carlos Olmeda-Gómez, 2021. "Mapping the intellectual structure of the coronavirus field (2000–2020): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6625-6657, August.
  29. Hao Wang & Sanhong Deng & Xinning Su, 2016. "A study on construction and analysis of discipline knowledge structure of Chinese LIS based on CSSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1725-1759, December.
  30. Blanca De-Miguel-Molina & Scott W. Cunningham & Fernando Palop, 2017. "Analyzing Funding Patterns and Their Evolution in Two Medical Research Topics," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(02), pages 1-39, April.
  31. Baker, H. Kent & Kumar, Satish & Pattnaik, Debidutta, 2021. "Twenty-five years of the Journal of Corporate Finance: A scientometric analysis," Journal of Corporate Finance, Elsevier, vol. 66(C).
  32. Sung Kim & Derek Hansen & Richard Helps, 2018. "Computing research in the academy: insights from theses and dissertations," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 135-158, January.
  33. Cristina Mele & Jaqueline Pels & Maria Spano & Irene Bernardo, 2023. "Emergent understandings of the market," Italian Journal of Marketing, Springer, vol. 2023(1), pages 1-25, March.
  34. Ahmed H. Alsharif & Nor Zafir Md Salleh & Rohaizat Baharun & Alharthi Rami Hashem E & Aida Azlina Mansor & Javed Ali & Alhamzah F. Abbas, 2021. "Neuroimaging Techniques in Advertising Research: Main Applications, Development, and Brain Regions and Processes," Sustainability, MDPI, vol. 13(11), pages 1-25, June.
  35. Yang, Zaoli & Zhang, Weijian & Yuan, Fei & Islam, Nazrul, 2021. "Measuring topic network centrality for identifying technology and technological development in online communities," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
  36. Shaista Rashid & Amira Khattak & Murtaza Ashiq & Shafiq Ur Rehman & Muhammad Rashid Rasool, 2021. "Educational Landscape of Virtual Reality in Higher Education: Bibliometric Evidences of Publishing Patterns and Emerging Trends," Publications, MDPI, vol. 9(2), pages 1-17, April.
  37. Lina PilelienÄ— & Ahmed H. Alsharif & Ibrahim Bader Alharbi, 2022. "Scientometric Analysis Of Scientific Literature On Neuromarketing Tools In Advertising," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 8(5).
  38. Yoshiaki Fujita & Michael S. Vitevitch, 2022. "Using network analyses to examine the extent to which and in what ways psychology is multidisciplinary," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
  39. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.
  40. Zhu, Lin & Cunningham, Scott W., 2022. "Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.