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[1] Loet Leydesdorff,et al. Co‐word maps and topic modeling: A comparison using small and medium‐sized corpora (N < 1,000) , 2015, J. Assoc. Inf. Sci. Technol..
[2] O A Rosso,et al. Distinguishing noise from chaos. , 2007, Physical review letters.
[3] Riccardo Torre,et al. Biblioranking fundamental physics , 2018, J. Informetrics.
[4] David C. Roberts,et al. Mapping the Evolution of Scientific Fields , 2009, PloS one.
[5] Ricardo López-Ruiz,et al. A Statistical Measure of Complexity , 1995, ArXiv.
[6] Benjamin Renoust,et al. Flows of Knowledge in Citation Networks , 2016, COMPLEX NETWORKS.
[7] Gilles Deleuze,et al. The Logic of Sense , 1969 .
[8] Osvaldo A. Rosso,et al. Generalized statistical complexity measures: Geometrical and analytical properties , 2006 .
[9] Nick S. Jones,et al. Co-occurrence simplicial complexes in mathematics: identifying the holes of knowledge , 2018, Appl. Netw. Sci..
[10] Saranya Ghosh,et al. General Model Independent Searches for Physics Beyond the Standard Model , 2020 .
[11] Lutz Bornmann,et al. Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis , 2017, Scientometrics.
[12] Jean-Gabriel Young,et al. Networks beyond pairwise interactions: structure and dynamics , 2020, ArXiv.
[13] Boleslaw K. Szymanski,et al. Quantifying patterns of research-interest evolution , 2017, Nature Human Behaviour.
[14] P. Langacker. The standard model and beyond , 2009 .
[15] M. Callon,et al. From translations to problematic networks: An introduction to co-word analysis , 1983 .
[16] Brenda Praggastis,et al. Hypernetwork Science: From Multidimensional Networks to Computational Topology , 2020, Unifying Themes in Complex Systems X.
[17] Maxima of Independent Sums in the Presence of Heavy Tails , 2005 .
[18] Kaveh Kavousi,et al. Predicting scientific research trends based on link prediction in keyword networks , 2020, J. Informetrics.
[19] Loet Leydesdorff,et al. A review of theory and practice in scientometrics , 2015, Eur. J. Oper. Res..
[20] S. Foss,et al. An Introduction to Heavy-Tailed and Subexponential Distributions , 2011 .
[21] Sebastián Lozano,et al. Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature , 2019, Scientometrics.
[22] Abbas Alimohammadi,et al. Mapping the intellectual structure of GIS-T field (2008–2019): a dynamic co-word analysis , 2021, Scientometrics.
[23] An Zeng,et al. Increasing trend of scientists to switch between topics , 2018, Nature Communications.
[24] Jean Pierre Courtial,et al. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry , 1991, Scientometrics.
[25] E. Todeva. Networks , 2007 .
[26] Michael Szell,et al. Taking census of physics , 2019, Nature Reviews Physics.
[27] Toni Giorgino,et al. Exploring the role of interdisciplinarity in physics: Success, talent and luck , 2019, PloS one.
[28] Luis Gravano,et al. Predicting the impact of scientific concepts using full‐text features , 2016, J. Assoc. Inf. Sci. Technol..
[29] Randall R. Holmes,et al. Introduction to Topology , 2008 .
[30] Olesya Mryglod,et al. Network of scientific concepts: empirical analysis and modeling , 2021, Adv. Complex Syst..
[31] Vincent D. Blondel,et al. Career on the Move: Geography, Stratification, and Scientific Impact , 2014, Scientific Reports.
[32] Wei Lu,et al. Keyword-citation-keyword network: a new perspective of discipline knowledge structure analysis , 2020, Scientometrics.
[33] Alessandro Vespignani,et al. Mapping the physics research space: a machine learning approach , 2019, EPJ Data Science.
[34] Siew Ann Cheong,et al. Predicting the Evolution of Physics Research from a Complex Network Perspective , 2018, Entropy.
[35] Matjaz Perc,et al. Self-organization of progress across the century of physics , 2013, Scientific Reports.
[36] Mario Coccia,et al. The evolution of scientific disciplines in applied sciences: dynamics and empirical properties of experimental physics , 2020, Scientometrics.
[37] Sagar Kamarthi,et al. Correction: Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature , 2017, PloS one.
[38] Mario Krenn,et al. Predicting research trends with semantic and neural networks with an application in quantum physics , 2019, Proceedings of the National Academy of Sciences.
[39] Anthony F. J. van Raan,et al. Measuring Science: Basic Principles and Application of Advanced Bibliometrics , 2019, Springer Handbook of Science and Technology Indicators.
[40] Alice Patania,et al. The shape of collaborations , 2017, EPJ Data Science.
[41] D. Bennett,et al. Visualizing context , 2008 .
[42] An Zeng,et al. The strong nonlinear effect in academic dropout , 2019, Scientometrics.
[43] Alexander M. Petersen,et al. Multiscale impact of researcher mobility , 2018, Journal of The Royal Society Interface.
[44] Jinho Choi,et al. The organization of scientific knowledge: the structural characteristics of keyword networks , 2011, Scientometrics.
[45] Vito Latora,et al. The evolution of knowledge within and across fields in modern physics , 2020, Scientific Reports.
[46] Mason A. Porter,et al. Random walks and diffusion on networks , 2016, ArXiv.
[47] Yurij L. Katchanov,et al. How physics works: scientific capital in the space of physics institutions , 2016, Scientometrics.
[48] Kevin C. Klement. Frege and the Logic of Sense and Reference , 2001 .
[49] Shuo Xu,et al. Review on emerging research topics with key-route main path analysis , 2019, Scientometrics.
[50] Linyuan Lu,et al. Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data , 2020, J. Informetrics.
[51] Diego Garlaschelli,et al. Ground truth? Concept-based communities versus the external classification of physics manuscripts , 2016, EPJ Data Science.
[52] Carl T. Bergstrom,et al. The Science of Science , 2018, Science.
[53] Michael Szell,et al. A century of physics , 2015, Nature Physics.
[54] Jari Saramäki,et al. The evolution of interdisciplinarity in physics research , 2012, Scientific Reports.
[55] Dietmar Wolfram,et al. Measuring Scholarly Impact: Methods and Practice , 2014 .
[56] Han Huang,et al. Evolutionary exploration and comparative analysis of the research topic networks in information disciplines , 2021, Scientometrics.
[57] Massimo Franceschet,et al. Clustering citation histories in the Physical Review , 2016, J. Informetrics.
[58] Francisco Herrera,et al. Journal of Informetrics , 2022 .
[59] Fabrizio Lillo,et al. Knowledge and social relatedness shape research portfolio diversification , 2020, Scientific Reports.
[60] Peter van den Besselaar,et al. Mapping science through bibliometric triangulation: An experimental approach applied to water research , 2017, J. Assoc. Inf. Sci. Technol..
[61] Yamir Moreno,et al. Explore with caution: mapping the evolution of scientific interest in physics , 2019, EPJ Data Science.
[62] Petr Matous,et al. Network of networks: A bibliometric analysis , 2021, Physica D: Nonlinear Phenomena.
[63] Danielle S. Bassett,et al. Architecture and evolution of semantic networks in mathematics texts , 2019, Proceedings of the Royal Society A.
[64] Mike Thelwall,et al. Springer Handbook of Science and Technology Indicators , 2019, Springer Handbook of Science and Technology Indicators.
[65] Cesar H. Comin,et al. How integrated are theoretical and applied physics? , 2017, Scientometrics.
[66] Yue Wang,et al. Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network , 2016 .
[67] Qian Zhang,et al. Characterizing scientific production and consumption in Physics , 2013, Scientific Reports.
[68] Peter A. Schulz,et al. Co-authorship networks and research impact in large research facilities: benchmarking internal reports and bibliometric databases , 2018, Scientometrics.
[69] Frank Schweitzer,et al. Citations driven by social connections? A multi-layer representation of coauthorship networks , 2019, Quantitative Science Studies.
[71] Young-Sun Jang,et al. How latecomers catch up to leaders in high-energy physics as Big Science: transition from national system to international collaboration , 2019, Scientometrics.
[72] Stasa Milojevic,et al. Quantifying the cognitive extent of science , 2015, J. Informetrics.
[73] Martina Iori,et al. New and atypical combinations: An assessment of novelty and interdisciplinarity , 2020 .
[74] H. Stanley,et al. The science of science: from the perspective of complex systems , 2017 .