{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:19:32Z","timestamp":1777889972552,"version":"3.51.4"},"reference-count":42,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T00:00:00Z","timestamp":1649203200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SW"],"published-print":{"date-parts":[[2022,4,6]]},"abstract":"<jats:p>Topic evolution helps the understanding of current research topics and their histories by automatically modeling and detecting the set of shared research fields in academic publications as topics. This paper provides a generalized analysis of the topic evolution method for predicting the emergence of new topics, which can operate on any dataset where the topics are defined as the relationships of their neighborhoods in the past by extrapolating to the future topics. Twenty sample topic networks were built with various fields-of-study keywords as seeds, covering domains such as business, materials, diseases, and computer science from the Microsoft Academic Graph dataset. The binary classifier was trained for each topic network using 15 structural features of emerging and existing topics and consistently resulted in accuracy and F1 over 0.91 for all twenty datasets over the periods of 2000 to 2019. Feature selection showed that the models retained most of the performance with only one-third of the tested features. Incremental learning was tested within the same topic over time and between different topics, which resulted in slight performance improvements in both cases. This indicates there is an underlying pattern to the neighbors of new topics common to research domains, likely beyond the sample topics used in the experiment. The result showed that network-based new topic prediction can be applied to various research domains with different research patterns.<\/jats:p>","DOI":"10.3233\/sw-212951","type":"journal-article","created":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T11:54:43Z","timestamp":1642161283000},"page":"423-439","source":"Crossref","is-referenced-by-count":8,"title":["Analyzing the generalizability of the network-based topic emergence identification method"],"prefix":"10.1177","volume":"13","author":[{"given":"Sukhwan","family":"Jung","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of South Alabama, 150 Student Services Dr, Mobile, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aviv","family":"Segev","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of South Alabama, 150 Student Services Dr, Mobile, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/SW-212951_ref1","doi-asserted-by":"publisher","DOI":"10.1184\/R1\/6626252.v1"},{"key":"10.3233\/SW-212951_ref2","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258108"},{"key":"10.3233\/SW-212951_ref3","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.techfore.2013.10.022","article-title":"The organisation of Corporate Foresight: A multiple case study in the telecommunication industry","volume":"87","author":"Battistella","year":"2014","journal-title":"Technological Forecasting and Social Change."},{"key":"10.3233\/SW-212951_ref4","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143859"},{"key":"10.3233\/SW-212951_ref5","first-page":"993","article-title":"Latent Dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"10.3233\/SW-212951_ref6","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.techfore.2013.12.007","article-title":"Measuring technological trends: A comparison between U.S. and U.S.S.R.\/Russian jet fighter aircraft","volume":"87","author":"Bongers","year":"2014","journal-title":"Technological Forecasting and Social Change."},{"key":"10.3233\/SW-212951_ref7","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.1016\/j.joi.2017.10.003","article-title":"Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval","volume":"11","author":"Chen","year":"2017","journal-title":"Journal of Informetrics."},{"key":"10.3233\/SW-212951_ref8","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1002\/asi.20317","article-title":"CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature","volume":"57","author":"Chen","year":"2006","journal-title":"Journal of the American Society for Information Science and Technology."},{"key":"10.3233\/SW-212951_ref9","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.70.066111"},{"key":"10.3233\/SW-212951_ref10","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1162\/tacl_a_00325","article-title":"Topic modeling in embedding spaces","volume":"8","author":"Dieng","year":"2020","journal-title":"Transactions of the Association for Computational Linguistics."},{"key":"10.3233\/SW-212951_ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273526"},{"key":"10.3233\/SW-212951_ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-0933-2_2"},{"key":"10.3233\/SW-212951_ref13","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1016\/j.ipm.2014.06.005","article-title":"Character n-gram application for automatic new topic identification","volume":"50","author":"Gencosman","year":"2014","journal-title":"Information Processing & Management."},{"key":"10.3233\/SW-212951_ref14","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972795.74"},{"key":"10.3233\/SW-212951_ref15","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1109\/TKDE.2013.56","article-title":"A two-level topic model towards knowledge discovery from citation networks","volume":"26","author":"Guo","year":"2014","journal-title":"IEEE Transactions on Knowledge and Data Engineering."},{"key":"10.3233\/SW-212951_ref16","doi-asserted-by":"publisher","DOI":"10.1145\/1645953.1646076"},{"key":"10.3233\/SW-212951_ref17","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/s11192-017-2247-8","volume":"111","author":"Hug","year":"2017","journal-title":"Citation Analysis with Microsoft Academic, Scientometrics."},{"key":"10.3233\/SW-212951_ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963444"},{"key":"10.3233\/SW-212951_ref19","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378277"},{"key":"10.3233\/SW-212951_ref20","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataCongress.2016.57"},{"key":"10.3233\/SW-212951_ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2513549.2513553"},{"key":"10.3233\/SW-212951_ref22","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.knosys.2014.04.036","article-title":"Analyzing future communities in growing citation networks","volume":"69","author":"Jung","year":"2014","journal-title":"Knowledge-Based Systems."},{"key":"10.3233\/SW-212951_ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.joi.2020.101040"},{"key":"10.3233\/SW-212951_ref24","doi-asserted-by":"publisher","first-page":"2432","DOI":"10.1002\/asi.23146","article-title":"Patent overlay mapping: Visualizing technological distance","volume":"65","author":"Kay","year":"2014","journal-title":"J Assn Inf Sci Tec."},{"key":"10.3233\/SW-212951_ref25","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1177\/0165551516661914","article-title":"Explore the research front of a specific research theme based on a novel technique of enhanced co-word analysis","volume":"43","author":"Li","year":"2017","journal-title":"Journal of Information Science."},{"key":"10.3233\/SW-212951_ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1081870.1081895"},{"key":"10.3233\/SW-212951_ref27","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.jengtecman.2013.09.001","article-title":"Comparing methods to extract technical content for technological intelligence","volume":"32","author":"Newman","year":"2014","journal-title":"Journal of Engineering and Technology Management."},{"key":"10.3233\/SW-212951_ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3148011.3148030"},{"key":"10.3233\/SW-212951_ref29","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1016\/j.ipm.2004.04.018","article-title":"Application of automatic topic identification on Excite Web search engine data logs","volume":"41","author":"Ozmutlu","year":"2005","journal-title":"Information Processing & Management."},{"key":"10.3233\/SW-212951_ref30","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1016\/j.ipm.2005.10.002","article-title":"Automatic new topic identification using multiple linear regression","volume":"42","author":"Ozmutlu","year":"2006","journal-title":"Information Processing & Management."},{"key":"10.3233\/SW-212951_ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-72150-7_19"},{"key":"10.3233\/SW-212951_ref32","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/0040-1625(95)00022-3","article-title":"Technology opportunities analysis","volume":"49","author":"Porter","year":"1995","journal-title":"Technological Forecasting and Social Change."},{"key":"10.3233\/SW-212951_ref33","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.119"},{"key":"10.3233\/SW-212951_ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3197026.3197052"},{"key":"10.3233\/SW-212951_ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30760-8_26"},{"key":"10.3233\/SW-212951_ref36","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.Congress.2013.65"},{"issue":"8","key":"10.3233\/SW-212951_ref37","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1109\/TSC.2014.2338855","article-title":"Analysis of technology trends based on diverse data sources","volume":"2015","author":"Segev","year":"2015","journal-title":"IEEE Transactions on Services Computing."},{"key":"10.3233\/SW-212951_ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2740908.2742839"},{"key":"10.3233\/SW-212951_ref40","unstructured":"M.\u00a0Steyvers and T.\u00a0Griffiths, Probabilistic topic models, in: Handbook of Latent Semantic Analysis, Lawrence Erlbaum Associates Publishers, Mahwah, NJ, US, 2007, pp.\u00a0427\u2013448."},{"key":"10.3233\/SW-212951_ref41","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2019.00045"},{"key":"10.3233\/SW-212951_ref42","unstructured":"J.\u00a0Zhang, Z.\u00a0Ghahramani and Y.\u00a0Yang, A probabilistic model for online document clustering with application to novelty detection, in: Proceedings of the 17th International Conference on Neural Information Processing Systems, MIT Press, Vancouver, British Columbia, Canada, 2004, pp.\u00a01617\u20131624."},{"key":"10.3233\/SW-212951_ref43","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1145\/279232.279236","article-title":"Algorithm\u00a0778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization","volume":"23","author":"Zhu","year":"1997","journal-title":"ACM Trans. Math. Softw."}],"container-title":["Semantic Web"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/SW-212951","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:26:21Z","timestamp":1777613181000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/SW-212951"}},"subtitle":[],"editor":[{"given":"Mehwish","family":"Alam","sequence":"additional","affiliation":[{"name":"FIZ Karlsruhe\u00a0\u2013 Leibniz Institute for Information Infrastructure, Germany"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Davide","family":"Buscaldi","sequence":"additional","affiliation":[{"name":"LIPN, Universit\u00e9 Sorbonne Paris Nord, France"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Michael","family":"Cochez","sequence":"additional","affiliation":[{"name":"Vrije University of Amsterdam, The Netherlands"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Francesco","family":"Osborne","sequence":"additional","affiliation":[{"name":"Knowledge Media Institute, (KMi), The Open University, UK"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Diego Reforgiato","family":"Recupero","sequence":"additional","affiliation":[{"name":"University of Cagliari, Italy"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Harald","family":"Sack","sequence":"additional","affiliation":[{"name":"FIZ Karlsruhe\u00a0\u2013 Leibniz Institute for Information Infrastructure, Germany"}],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Mehwish","family":"Alam","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Davide","family":"Buscaldi","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Michael","family":"Cochez","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Francesco","family":"Osborne","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Diego","family":"Refogiato Recupero","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Harald","family":"Sack","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2022,4,6]]},"references-count":42,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/sw-212951","relation":{},"ISSN":["2210-4968","1570-0844"],"issn-type":[{"value":"2210-4968","type":"electronic"},{"value":"1570-0844","type":"print"}],"subject":[],"published":{"date-parts":[[2022,4,6]]}}}