This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Bartol, T., Budimir, G., Juznic, P., & Stopar, K. (2016). Mapping and classification of agriculture in Web of Science: Other subject categories and research fields may benefit. Scientometrics, 109(2), 979–996.BartolT.BudimirG.JuznicP.StoparK.2016Mapping and classification of agriculture in Web of Science: Other subject categories and research fields may benefit109297999610.1007/s11192-016-2071-6Search in Google Scholar
Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. Third international AAAI conference on weblogs and social media.BastianM.HeymannS.JacomyM.2009Third international AAAI conference on weblogs and social mediaSearch in Google Scholar
Bornmann, L., Leydesdorff, L., Walch-Solimena, C., & Ettl, C. (2011). Mapping excellence in the geography of science: An approach based on Scopus data. Journal of Informetrics, 5(4), 537–546.BornmannL.LeydesdorffL.Walch-SolimenaC.EttlC.2011Mapping excellence in the geography of science: An approach based on Scopus data5453754610.1016/j.joi.2011.05.005Search in Google Scholar
Boyack, K.W., & Klavans, R. (2014). Creation of a highly detailed, dynamic, global model and map of science. Journal of the Association for Information Science and Technology, 65(4), 670–685. doi: 10.1002/asi.22990, URL https://dx.doi.org/10.1002/asi.22990BoyackK.W.KlavansR.2014Creation of a highly detailed, dynamic, global model and map of science65467068510.1002/asi.22990URL https://dx.doi.org/10.1002/asi.22990Open DOISearch in Google Scholar
Boyack, K.W., Klavans, R., & Börner, K. (2005). Mapping the backbone of science. Scientometrics, 64(3), 351–374.BoyackK.W.KlavansR.BörnerK.2005Mapping the backbone of science64335137410.1007/s11192-005-0255-6Search in Google Scholar
Boyack, K.W., Newman, D., Duhon, R.J., Klavans, R., Patek, M., Biberstine, J.R., Schijvenaars, B., Skupin, A., Ma, N., & Börner, K. (2011). Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches. PLoS ONE, 6(3), e18029–e18029. doi: 10.1371/journal.pone.0018029BoyackK.W.NewmanD.DuhonR.J.KlavansR.PatekM.BiberstineJ.R.SchijvenaarsB.SkupinA.MaN.BörnerK.2011Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches63e18029e1802910.1371/journal.pone.0018029Open DOISearch in Google Scholar
Boyack, K.W., Small, H., & Klavans, R. (2013). Improving the accuracy of co-citation clustering using full text. Journal of the American Society for Information Science and Technology, 64(9), 1759–1767. doi: 10.1002/asi.22896BoyackK.W.SmallH.KlavansR.2013Improving the accuracy of co-citation clustering using full text6491759176710.1002/asi.22896Open DOISearch in Google Scholar
Chen, C.M. (1999). Visualising semantic spaces and author co-citation networks in digital libraries. Information Processing & Management, 35(3), 401–420.ChenC.M.1999Visualising semantic spaces and author co-citation networks in digital libraries35340142010.1016/S0306-4573(98)00068-5Search in Google Scholar
Chen, T. (2020). Essential Science Indicators highly cited paper co-citation relationships 2018.3. V1. DOI http://www.dx.doi.org/10.11922/sciencedb.00256, URL http://www.dx.doi.org/10.11922/sciencedb.00256ChenT.2020DOI http://www.dx.doi.org/10.11922/sciencedb.00256, URL http://www.dx.doi.org/10.11922/sciencedb.00256Search in Google Scholar
Chen, T., Wang, H., & Wang, X. (2020). Detecting Funding Topics Evolutions with Visualization (in Chinese). Data Analysis and Knowledge Discovery, 4(2/3).ChenT.WangH.WangX.2020Detecting Funding Topics Evolutions with Visualization (in Chinese)42/3Search in Google Scholar
van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.van EckN.J.WaltmanL.2010Software survey: VOSviewer, a computer program for bibliometric mapping84252353810.1007/s11192-009-0146-3288393220585380Search in Google Scholar
van Eck, N.J., Waltman, L., Noyons, E.C.M., & Buter, R.K. (2010). Automatic term identification for bibliometric mapping. Scientometrics, 82(3), 581–596.van EckN.J.WaltmanL.NoyonsE.C.M.ButerR.K.2010Automatic term identification for bibliometric mapping82358159610.1007/s11192-010-0173-0283058620234767Search in Google Scholar
Gibson, H., Faith, J., & Vickers, P. (2013). A survey of two-dimensional graph layout techniques for information visualisation. Information Visualization, 12(3–4), 324–357.GibsonH.FaithJ.VickersP.2013A survey of two-dimensional graph layout techniques for information visualisation123–432435710.1177/1473871612455749Search in Google Scholar
Grover, A., & Leskovec, J. (2016). Node2Vec: Scalable feature learning for networks. In Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, pp 855–864.GroverA.LeskovecJ.2016Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data miningACM85586410.1145/2939672.2939754510865427853626Search in Google Scholar
Katsurai, M., & Ono, S. (2019). TrendNets: Mapping emerging research trends from dynamic co-word networks via sparse representation. Scientometrics, 121(3), 1583–1598.KatsuraiM.OnoS.2019TrendNets: Mapping emerging research trends from dynamic co-word networks via sparse representation12131583159810.1007/s11192-019-03241-6Search in Google Scholar
Kruskal, J.B. (1977). Multidimensional scaling and other methods for discovery structure. In: Enslein, K., Ralston, A., & Wilf, H. (eds) Statistical methods for digital computers, Wiley.KruskalJ.B.1977Multidimensional scaling and other methods for discovery structureIn:EnsleinK.RalstonA.WilfH.(eds)WileySearch in Google Scholar
Kullback, S., & Leibler, R.A. (1951). On Information and Sufficiency. The Annals of Mathematical Statistics, 22(1), 79–86. doi: 10.1214/aoms/1177729694KullbackS.LeiblerR.A.1951On Information and Sufficiency221798610.1214/aoms/1177729694Open DOISearch in Google Scholar
Le, Q., & Mikolov, T. (2014). Distributed representations of sentences and documents. In Proceedings of the 31st International Conference on Machine Learning, pp 1188–1196.LeQ.MikolovT.2014InProceedings of the 31st International Conference on Machine Learning11881196Search in Google Scholar
Li, P., Yang, G.L., & Wang, C.Q. (2019). Visual topical analysis of library and information science. Scientometrics, 121, 1753–1791.LiP.YangG.L.WangC.Q.2019Visual topical analysis of library and information science1211753179110.1007/s11192-019-03239-0Search in Google Scholar
Li, W.T., Cerise, J.E., Yang, Y.N., & Han, H. (2017). Application of t-SNE to human genetic data. Journal of Bioinformatics and Computational Biology, 15(4), 1750017–1750017.LiW.T.CeriseJ.E.YangY.N.HanH.2017Application of t-SNE to human genetic data1541750017175001710.1142/S021972001750017228718343Search in Google Scholar
Liu, S., Bremer, P.T., Thiagarajan, J.J., Srikumar, V., Wang, B., Livnat, Y., & Pascucci, V. (2018). Visual Exploration of Semantic Relationships in Neural Word Embeddings. IEEE Transactions on Visualization and Computer Graphics, 24(1), 553–562.LiuS.BremerP.T.ThiagarajanJ.J.SrikumarV.WangB.LivnatY.PascucciV.2018Visual Exploration of Semantic Relationships in Neural Word Embeddings24155356210.1109/TVCG.2017.274514128866574Search in Google Scholar
Liu, Z. (1992). Visualizing the intellectual structure in urban studies: A journal co-citation analysis. Scientometrics, 62(3), 385–402.LiuZ.1992Visualizing the intellectual structure in urban studies: A journal co-citation analysis62338540210.1007/s11192-005-0029-1Search in Google Scholar
Maaten, L.V.D., & Hinton, G. (2008). Visualizing data using t-SNE. Journal of Machine Learning Research, 9, 2579–2605.MaatenL.V.D.HintonG.2008Visualizing data using t-SNE925792605Search in Google Scholar
Martin, S., Brown, W.M., Klavans, R., & Boyack, K.W. (2011). OpenOrd: An open-source toolbox for large graph layout. International Society for Optics and Photonics, 7868, 786806–786806.MartinS.BrownW.M.KlavansR.BoyackK.W.2011OpenOrd: An open-source toolbox for large graph layout786878680678680610.1117/12.871402Search in Google Scholar
Perozzi, B., Al-Rfou, R., & Skiena, S. (2014). Deepwalk: Online learning of social representations. In: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, pp 701–710.PerozziB.Al-RfouR.SkienaS.2014In:Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data miningACM70171010.1145/2623330.2623732Search in Google Scholar
Pezzotti, N., Lelieveldt, B.P.F., van der Maaten, L., Hollt, T., Eisemann, E., & Vilanova, A. (2017). Approximated and User Steerable tSNE for Progressive Visual Analytics. IEEE Transactions on Visualization and Computer Graphics, 23(7), 1739–1752.PezzottiN.LelieveldtB.P.F.van der MaatenL.HolltT.EisemannE.VilanovaA.2017Approximated and User Steerable tSNE for Progressive Visual Analytics2371739175210.1109/TVCG.2016.257075528113434Search in Google Scholar
Shen, Z.S., Chen, F.Y., Yang, L.Y., & Wu, J.S. (2019). Node2vec representation for clustering journals and as a possible measure of diversity. Journal of Data and Information Science, 4(2), 79–92.ShenZ.S.ChenF.Y.YangL.Y.WuJ.S.2019Node2vec representation for clustering journals and as a possible measure of diversity42799210.2478/jdis-2019-0010Search in Google Scholar
Small, H. (1999). Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799–813.SmallH.1999Visualizing science by citation mapping50979981310.1002/(SICI)1097-4571(1999)50:9<799::AID-ASI9>3.0.CO;2-GSearch in Google Scholar
Small, H., & Griffith, B.C. (1974). The Structure of Scientific Literatures I: Identifying and Graphing Specialties. Science Studies, 4(1), 17–40.SmallH.GriffithB.C.1974The Structure of Scientific Literatures I: Identifying and Graphing Specialties41174010.1177/030631277400400102Search in Google Scholar
Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., & Mei, Q. (2015). Line: Large-scale information network embedding. In: Proceedings of the 24th international conference on world wide web, WWW, pp 1067–1077.TangJ.QuM.WangM.ZhangM.YanJ.MeiQ.2015In:Proceedings of the 24th international conference on world wide web, WWW1067107710.1145/2736277.2741093Search in Google Scholar
Wang, X., Han, T., Li, G., Chen, T., & Zhang, X. (2017). Mapping science structure 2017 (in Chinese). Science Press China.WangX.HanT.LiG.ChenT.ZhangX.2017Science PressChinaSearch in Google Scholar
White, H.D. (2003). Pathfinder networks and author co-citation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science, 54(5), 423–434.WhiteH.D.2003Pathfinder networks and author co-citation analysis: A remapping of paradigmatic information scientists54542343410.1002/asi.10228Search in Google Scholar
Zhai, T., & Di, L.Z. (2019). Information mining and visualization of highly cited papers on type-2 diabetes mellitus from ESI. CURRENT SCIENCE, 116(12), 1965.ZhaiT.DiL.Z.2019Information mining and visualization of highly cited papers on type-2 diabetes mellitus from ESI11612196510.18520/cs/v116/i12/1965-1974Search in Google Scholar
Zhou, Q., & Leydesdorff, L. (2016). The normalization of occurrence and Co-occurrence matrices in bibliometrics using Cosinesimilarities and Ochiaicoefficients. Journal of the Association for Information Science and Technology, 67(11), 2805–2814. doi: 10.1002/asi.23603ZhouQ.LeydesdorffL.2016The normalization of occurrence and Co-occurrence matrices in bibliometrics using Cosinesimilarities and Ochiaicoefficients67112805281410.1002/asi.23603Open DOISearch in Google Scholar