Vol.:(0123456789) Scientometrics https://doi.org/10.1007/s11192-019-03036-9 1 3 Tracing the ‘swan groups’ of physics and economics in the key publications of nobel laureates Helena H. Zhang 1,2,3  · Alesia A. Zuccala 4  · Fred Y. Ye 1,2,3 Received: 17 September 2018 © Akadémiai Kiadó, Budapest, Hungary 2019 Abstract Following the ‘black–white swan’ interaction metaphor introduced in an earlier study, we now trace and observe a new ‘swan groups’ pattern. Our motivation for introducing the ‘swan groups’ is based on the fact that ‘black–white swan’ interactions are observed pri- marily in physics, which belongs to science. We extend a newer model called ‘swan groups’ model and test its applicability to the feld of economics, belonging to social sciences. The primary feature of this model is that the ‘black swan’ represents an important scientifc discovery or contribution that has been awarded Nobel Prize, while the ‘white swans’ are highly cited publications by the ‘black swan’. Together the two types of swans form a group, though unlike the original ‘black–white swan’ interaction pattern, the ‘swan groups’ do not necessarily interact in a way where we see a marked decrease in citations to white swans. Our fndings show that the new ‘swan groups’ pattern covers about 50% of key Nobel prize-winning physics papers and about 40% of key Nobel prize-winning economic papers. This allows us to identify important academic achievements both qualitatively and quantitatively, not only in science where major breakthroughs can cause paradigm shifts, but also in the social sciences where progress often remains open to multiple discoveries and doctrines. Keywords Swan groups · White swans · Black swan · Scientifc metrics · Nobel prize Helena H. Zhang and Alesia A. Zuccala have contribute equally and are listed alphabetically. * Fred Y. Ye yye@nju.edu.cn 1 International Joint Informatics Laboratory (IJIL), Nanjing University, Nanjing, China 2 International Joint Informatics Laboratory (IJIL), University of Illinois, Champaign, USA 3 Jiangsu Key Laboratory of Data Engineering and Knowledge Service, School of Information Management, Nanjing University, Nanjing 210023, China 4 Department Information Studies, University of Copenhagen, 2300 Copenhagen, Denmark