Which publication is your representative work?. Issue 3 (August 2016)

• Record Type: Journal Article
• Authors: Niu, Qikai; Zhou, Jianlin; Zeng, An; Fan, Ying; Di, Zengru
• Is Part Of: Journal of informetrics. Volume 10:Issue 3(2016:Jul.)
• Page Start: 842
• Page End: 853
• Publication Date: 2016-08
• Subjects: Representative work -- Self-avoiding preferential diffusion -- Citation networks; Library statistics -- Periodicals; Information science -- Statistical methods -- Periodicals; Bibliometrics -- Periodicals; Bibliothèques -- Statistiques -- Périodiques; Sciences de l'information -- Méthodes statistiques -- Périodiques; Bibliométrie -- Périodiques; 020.727
• DOI: 10.1016/j.joi.2016.06.001
• Languages: English
• ISSNs: 1751-1577

Abstract

Abstract : Highlights: We propose a diffusion method to identify the representative work for individual authors. Our method outperforms the PageRank and citation count methods. Our method is very robust against name ambiguity. Research patterns of scientists can be revealed by our diffusion method. The method can be extended to journals, institutes and countries. Abstract: As much effort has been made to accelerate the publication of research results, nowadays the number of papers per scientist is much larger than before. In this context, how to identify the representative work for individual researcher is an important yet uneasy problem. Addressing it will help policy makers better evaluate the achievement and potential of researchers. So far, the representative work of a researcher is usually selected as his/her most highly cited paper or the paper published in top journals. Here, we consider the representative work of a scientist as an important paper in his/her area of expertise. Accordingly, we propose a self-avoiding preferential diffusion process to generate personalized ranking of papers for each scientist and identify their representative works. The citation data from American Physical Society (APS) are used to validate our method. We find that the self-avoiding preferential diffusion method can rank the Nobel prize winning paper in each Nobel laureate's personal ranking list higher than the citation count and PageRank methods, indicating the effectiveness of our method. Moreover, the robustness analysis shows that our method can highly rank the representative papers of scientists even if partial citation data are available or spurious behaviors exist. The method is finally applied to revealing the research patterns (i.e. consistency-oriented or diversity-oriented) of different scientists, institutes and countries.