IDEAS home Printed from https://ideas.repec.org/r/bla/jamist/v62y2011i2p236-245.html
   My bibliography  Save this item

Applying weighted PageRank to author citation networks

Citations

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


Cited by:

  1. Ding, Ying & Liu, Xiaozhong & Guo, Chun & Cronin, Blaise, 2013. "The distribution of references across texts: Some implications for citation analysis," Journal of Informetrics, Elsevier, vol. 7(3), pages 583-592.
  2. Yanbo Zhou & Xin-Li Xu & Xu-Hua Yang & Qu Li, 2022. "The influence of disruption on evaluating the scientific significance of papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5931-5945, October.
  3. Wenjia Zhu & Jiancheng Guan, 2013. "A bibliometric study of service innovation research: based on complex network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1195-1216, March.
  4. Nykl, Michal & Ježek, Karel & Fiala, Dalibor & Dostal, Martin, 2014. "PageRank variants in the evaluation of citation networks," Journal of Informetrics, Elsevier, vol. 8(3), pages 683-692.
  5. Nisar Ali & Zahid Halim & Syed Fawad Hussain, 2023. "An artificial intelligence-based framework for data-driven categorization of computer scientists: a case study of world’s Top 10 computing departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1513-1545, March.
  6. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
  7. Yanan Wang & An Zeng & Ying Fan & Zengru Di, 2019. "Ranking scientific publications considering the aging characteristics of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 155-166, July.
  8. Zhang, Panpan & Wang, Tiandong & Yan, Jun, 2022. "PageRank centrality and algorithms for weighted, directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
  9. Wang, Shuliang & Sun, Jingya & Zhang, Jianhua & Dong, Qiqi & Gu, Xifeng & Chen, Chen, 2023. "Attack-Defense game analysis of critical infrastructure network based on Cournot model with fixed operating nodes," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
  10. Fiala, Dalibor & Šubelj, Lovro & Žitnik, Slavko & Bajec, Marko, 2015. "Do PageRank-based author rankings outperform simple citation counts?," Journal of Informetrics, Elsevier, vol. 9(2), pages 334-348.
  11. Zhang, Fang & Wu, Shengli, 2020. "Predicting future influence of papers, researchers, and venues in a dynamic academic network," Journal of Informetrics, Elsevier, vol. 14(2).
  12. Dinesh Pradhan & Partha Sarathi Paul & Umesh Maheswari & Subrata Nandi & Tanmoy Chakraborty, 2017. "$$C^3$$ C 3 -index: a PageRank based multi-faceted metric for authors’ performance measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 253-273, January.
  13. Zeng, Tong & Wu, Longfeng & Bratt, Sarah & Acuna, Daniel E., 2020. "Assigning credit to scientific datasets using article citation networks," Journal of Informetrics, Elsevier, vol. 14(2).
  14. Jin Sung Rha, 2020. "Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis," Sustainability, MDPI, vol. 12(11), pages 1-27, May.
  15. A. V. Chumachenko & B. G. Kreminskyi & Iu. L. Mosenkis & A. I. Yakimenko, 2020. "Dynamics of topic formation and quantitative analysis of hot trends in physical science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 739-753, October.
  16. Zhao, Star X. & Ye, Fred Y., 2012. "Exploring the directed h-degree in directed weighted networks," Journal of Informetrics, Elsevier, vol. 6(4), pages 619-630.
  17. Jianlin Zhou & An Zeng & Ying Fan & Zengru Di, 2016. "Ranking scientific publications with similarity-preferential mechanism," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 805-816, February.
  18. Stephany, Fabian & Teutloff, Ole & Lehdonvirta, Vili, 2022. "What is the price of a skill? Revealing the complementary value of skills," MPRA Paper 114874, University Library of Munich, Germany.
  19. Dejian Yu & Wanru Wang & Shuai Zhang & Wenyu Zhang & Rongyu Liu, 2017. "A multiple-link, mutually reinforced journal-ranking model to measure the prestige of journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 521-542, April.
  20. Dietmar Wolfram, 2015. "The symbiotic relationship between information retrieval and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2201-2214, March.
  21. Nadia Simoes & Nuno Crespo, 2020. "A flexible approach for measuring author-level publishing performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 331-355, January.
  22. Yubing Nie & Yifan Zhu & Qika Lin & Sifan Zhang & Pengfei Shi & Zhendong Niu, 2019. "Academic rising star prediction via scholar’s evaluation model and machine learning techniques," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 461-476, August.
  23. Chen, Ying & Koch, Thorsten & Zakiyeva, Nazgul & Liu, Kailiang & Xu, Zhitong & Chen, Chun-houh & Nakano, Junji & Honda, Keisuke, 2023. "Article’s scientific prestige: Measuring the impact of individual articles in the web of science," Journal of Informetrics, Elsevier, vol. 17(1).
  24. Fiala, Dalibor, 2012. "Time-aware PageRank for bibliographic networks," Journal of Informetrics, Elsevier, vol. 6(3), pages 370-388.
  25. Nykl, Michal & Campr, Michal & Ježek, Karel, 2015. "Author ranking based on personalized PageRank," Journal of Informetrics, Elsevier, vol. 9(4), pages 777-799.
  26. Hao Wang & Hua-Wei Shen & Xue-Qi Cheng, 2016. "Scientific credit diffusion: Researcher level or paper level?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 827-837, November.
  27. Scholz, Michael & Pfeiffer, Jella & Rothlauf, Franz, 2017. "Using PageRank for non-personalized default rankings in dynamic markets," European Journal of Operational Research, Elsevier, vol. 260(1), pages 388-401.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.