{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T22:22:55Z","timestamp":1765232575754},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T00:00:00Z","timestamp":1524614400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T00:00:00Z","timestamp":1524614400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Comput"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s11047-018-9681-2","type":"journal-article","created":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T04:46:10Z","timestamp":1524631570000},"page":"547-575","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Swarm optimization clustering methods for opinion mining"],"prefix":"10.1007","volume":"19","author":[{"given":"Ellen","family":"Souza","sequence":"first","affiliation":[]},{"given":"Diego","family":"Santos","sequence":"additional","affiliation":[]},{"given":"Gustavo","family":"Oliveira","sequence":"additional","affiliation":[]},{"given":"Alisson","family":"Silva","sequence":"additional","affiliation":[]},{"given":"Adriano L. I.","family":"Oliveira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,4,25]]},"reference":[{"key":"9681_CR1","unstructured":"Abbasi A, Hassan A, Dhar M (2014) Benchmarking Twitter sentiment analysis tools. In: Proceedings of LREC-2014, the ninth international conference on language resources and evaluation, March, pp 823\u2013829"},{"key":"9681_CR2","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.inffus.2015.06.002","volume":"27","author":"JA Balazs","year":"2016","unstructured":"Balazs JA, Vel\u00e1squez JD (2016) Opinion mining and information fusion: a survey. Inf Fusion 27:95\u2013110. \n                  https:\/\/doi.org\/10.1016\/j.inffus.2015.06.002","journal-title":"Inf Fusion"},{"key":"9681_CR3","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.ins.2013.12.010","volume":"265","author":"L Cagnina","year":"2014","unstructured":"Cagnina L, Errecalde M, Ingaramo D, Rosso P (2014) An efficient particle swarm optimization approach to cluster short texts. Inf Sci 265:36\u201349. \n                  https:\/\/doi.org\/10.1016\/j.ins.2013.12.010","journal-title":"Inf Sci"},{"key":"9681_CR4","unstructured":"Cagnina LC, Errecalde ML, Ingaramo DA (2008) A discrete particle swarm optimizer for clustering short-text corpora. In: Proceedings of international conference on bioinspired optimization methods and their applications, BIOMA 2008, pp 1\u201310"},{"key":"9681_CR5","doi-asserted-by":"publisher","unstructured":"Coletta LFS, d\u00a0Silva NFF, Hruschka ER, Hruschka ER (2014) Combining classification and clustering for tweet sentiment analysis. In: Brazilian conference on intelligent systems, pp 210\u2013215. \n                  https:\/\/doi.org\/10.1109\/BRACIS.2014.46","DOI":"10.1109\/BRACIS.2014.46"},{"key":"9681_CR6","unstructured":"ComScore (2016) Comscore: cross-platform measurement company. \n                  http:\/\/www.comscore.com\/"},{"key":"9681_CR7","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1017\/CBO9781316212530.011","volume-title":"Linkage criteria for agglomerative hierarchical clustering","author":"B Cornwell","year":"2015","unstructured":"Cornwell B (2015) Linkage criteria for agglomerative hierarchical clustering. Cambridge University Press, Cambridge, pp 270\u2013274. \n                  https:\/\/doi.org\/10.1017\/CBO9781316212530.011\n                  \n                 Structural Analysis in the Social Sciences,"},{"key":"9681_CR8","unstructured":"Cui X, Potok TE (2005) Document clustering analysis based on hybrid pso+k-means algorithm. Special issue, pp 27\u201333"},{"key":"9681_CR9","doi-asserted-by":"publisher","unstructured":"Cui X, Potok TE, Palathingal P (2005) Document clustering using particle swarm optimization. In: Proceedings 2005 IEEE swarm intelligence symposium, pp 185\u2013191. \n                  https:\/\/doi.org\/10.1109\/SIS.2005.1501621","DOI":"10.1109\/SIS.2005.1501621"},{"key":"9681_CR10","unstructured":"Evangelista TR, Padilha TPP (2013) Monitoramento de Posts Sobre Empresas de E-Commerce em Redes Sociais Utilizando An\u00e1lise de Sentimentos. Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)"},{"issue":"4","key":"9681_CR11","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1145\/2436256.2436274","volume":"56","author":"R Feldman","year":"2013","unstructured":"Feldman R (2013) Techniques and applications for sentiment analysis. Commun ACM 56(4):82\u201389. \n                  https:\/\/doi.org\/10.1145\/2436256.2436274","journal-title":"Commun ACM"},{"key":"9681_CR12","doi-asserted-by":"publisher","first-page":"6315","DOI":"10.1016\/j.eswa.2015.04.032","volume":"42","author":"TMS Filho","year":"2015","unstructured":"Filho TMS, Pimentel BA, Souza RM, Oliveira AL (2015) Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization. Expert Syst Appl 42:6315\u20136328. \n                  https:\/\/doi.org\/10.1016\/j.eswa.2015.04.032","journal-title":"Expert Syst Appl"},{"issue":"7","key":"9681_CR13","doi-asserted-by":"publisher","first-page":"2889","DOI":"10.1007\/s00500-015-1951-7","volume":"20","author":"N Fouladgar","year":"2016","unstructured":"Fouladgar N, Lotfi S (2016) A novel approach for optimization in dynamic environments based on modified cuckoo search algorithm. Soft Comput 20(7):2889\u20132903","journal-title":"Soft Comput"},{"key":"9681_CR14","unstructured":"Go A, Bhayani R, Huang L (2010) Twitter Sentiment classification using distant supervision. Tech rep"},{"issue":"2","key":"9681_CR15","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1080\/19475683.2016.1144648","volume":"22","author":"Y Huang","year":"2016","unstructured":"Huang Y (2016) Conceptually categorizing geographic features from text based on latent semantic analysis and ontologies. Ann GIS 22(2):113\u2013127","journal-title":"Ann GIS"},{"issue":"1","key":"9681_CR16","doi-asserted-by":"publisher","first-page":"3","DOI":"10.3233\/978-1-60750-010-0-3","volume":"196","author":"D Ingaramo","year":"2009","unstructured":"Ingaramo D, Errecalde M, Cagnina L, Rosso P (2009) Particle swarm optimization for clustering short-text corpora. Front Artif Intell Appl 196(1):3\u201319. \n                  https:\/\/doi.org\/10.3233\/978-1-60750-010-0-3","journal-title":"Front Artif Intell Appl"},{"issue":"Icl","key":"9681_CR17","first-page":"43","volume":"824","author":"D Ingaramo","year":"2011","unstructured":"Ingaramo D, Errecalde M, Cagnina L, Rosso P (2011) A particle swarm optimizer to cluster parallel Spanish\u2013English short-text corpora. CEUR Workshop Proc 824(Icl):43\u201348","journal-title":"CEUR Workshop Proc"},{"key":"9681_CR18","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1007\/978-3-319-23207-2","volume":"388","author":"N Kamel","year":"2016","unstructured":"Kamel N, Ouchen I, Baali K (2016) A sampling-PSO-K-means algorithm for document clustering. Adv Intell Syst Comput 388:405\u2013411. \n                  https:\/\/doi.org\/10.1007\/978-3-319-23207-2","journal-title":"Adv Intell Syst Comput"},{"issue":"3","key":"9681_CR19","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","volume":"39","author":"D Karaboga","year":"2007","unstructured":"Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm. J Global Optim 39(3):459\u2013471","journal-title":"J Global Optim"},{"issue":"2","key":"9681_CR20","doi-asserted-by":"publisher","first-page":"69","DOI":"10.2478\/s13537-013-0104-2","volume":"3","author":"S Karol","year":"2013","unstructured":"Karol S, Mangat V (2013) Evaluation of text document clustering approach based on particle swarm optimization. Cent Eur J Comp Sci 3(2):69\u201390. \n                  https:\/\/doi.org\/10.2478\/s13537-013-0104-2","journal-title":"Cent Eur J Comp Sci"},{"key":"9681_CR21","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. In: IEEE international conference on systems, man, and cybernetics, pp 4\u20138","DOI":"10.1109\/ICSMC.1997.637339"},{"key":"9681_CR22","unstructured":"Kushal D, Lawrence S, Pennock DM (2003) Mining the peanut gallery: opinion extraction and semantic classification of product reviews. In: WWW, pp 519\u2013528"},{"key":"9681_CR23","doi-asserted-by":"publisher","unstructured":"Li G, Liu F (2010) A clustering-based approach on sentiment analysis. In: International conference on intelligent systems and knowledge engineering (ISKE), pp 331\u2013337. \n                  https:\/\/doi.org\/10.1109\/ISKE.2010.5680859","DOI":"10.1109\/ISKE.2010.5680859"},{"issue":"2","key":"9681_CR24","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1177\/0165551511432670","volume":"38","author":"G Li","year":"2012","unstructured":"Li G, Liu F (2012) Application of a clustering method on sentiment analysis. J Inf Sci 38(2):127\u2013139. \n                  https:\/\/doi.org\/10.1177\/0165551511432670","journal-title":"J Inf Sci"},{"issue":"3","key":"9681_CR25","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/s10489-013-0463-3","volume":"40","author":"G Li","year":"2014","unstructured":"Li G, Liu F (2014) Sentiment analysis based on clustering: a framework in improving accuracy and recognizing neutral opinions. Appl Intell 40(3):441\u2013452. \n                  https:\/\/doi.org\/10.1007\/s10489-013-0463-3","journal-title":"Appl Intell"},{"key":"9681_CR26","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/978-1-4614-3223-4_13","volume":"1","author":"B Liu","year":"2012","unstructured":"Liu B, Zhang L (2012) A survey of opinion mining and sentiment analysis. Min Text Data Chapter 1:415\u2013463","journal-title":"Min Text Data Chapter"},{"key":"9681_CR27","unstructured":"MacQueen J et al (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, Oakland, CA, USA 1:281\u2013297"},{"key":"9681_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdmm.2015.06.004","author":"E Marine-Roig","year":"2015","unstructured":"Marine-Roig E, Anton Clav\u00e9 S (2015) Tourism analytics with massive user-generated content: a case study of Barcelona. J Destin Mark Manag. \n                  https:\/\/doi.org\/10.1016\/j.jdmm.2015.06.004","journal-title":"J Destin Mark Manag"},{"key":"9681_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-11313-5","author":"C Marques-lucena","year":"2015","unstructured":"Marques-lucena C, Sarraipa J (2015) Framework for customers sentiment analysis. Adv Intell Syst Comput. \n                  https:\/\/doi.org\/10.1007\/978-3-319-11313-5","journal-title":"Adv Intell Syst Comput"},{"issue":"4","key":"9681_CR30","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1016\/j.asej.2014.04.011","volume":"5","author":"W Medhat","year":"2014","unstructured":"Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithms and applications: a survey. Ain Shams Eng J 5(4):1093\u20131113. \n                  https:\/\/doi.org\/10.1016\/j.asej.2014.04.011","journal-title":"Ain Shams Eng J"},{"issue":"10","key":"9681_CR31","doi-asserted-by":"publisher","first-page":"4241","DOI":"10.1016\/j.eswa.2013.01.019","volume":"40","author":"MM Mostafa","year":"2013","unstructured":"Mostafa MM (2013) More than words: social networks text mining for consumer brand sentiments. Expert Syst Appl 40(10):4241\u20134251. \n                  https:\/\/doi.org\/10.1016\/j.eswa.2013.01.019","journal-title":"Expert Syst Appl"},{"key":"9681_CR32","unstructured":"Owoputi O, Connor BO, Dyer C, Gimpel K, Schneider N (2012) Part-of-speech tagging for Twitter: word clusters and other advances. Carnegie Mellon University, Tech rep"},{"key":"9681_CR33","doi-asserted-by":"publisher","unstructured":"Pak A, Paroubek P (2010) Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of LREC, pp 1320\u20131326. \n                  https:\/\/doi.org\/10.1371\/journal.pone.0026624","DOI":"10.1371\/journal.pone.0026624"},{"key":"9681_CR34","doi-asserted-by":"publisher","unstructured":"Pang B, Lee L (2005) Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. In: Proceedings of the 43rd annual meeting on association for computational linguistics, ACL \u201905, pp 115\u2013124. \n                  https:\/\/doi.org\/10.3115\/1219840.1219855","DOI":"10.3115\/1219840.1219855"},{"issue":"12","key":"9681_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/1500000011","volume":"2","author":"B Pang","year":"2008","unstructured":"Pang B, Lee L (2008) Opinion mining and sentiment analysis. Found Trends Inf Retr 2(12):1\u2013135. \n                  https:\/\/doi.org\/10.1561\/1500000011","journal-title":"Found Trends Inf Retr"},{"key":"9681_CR36","doi-asserted-by":"crossref","unstructured":"Pang B, Lee L, Vaithyanathan S (2002) Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the conference on empirical methods in natural language processing (EMNLP) (July), pp 79\u201386","DOI":"10.3115\/1118693.1118704"},{"issue":"1","key":"9681_CR37","first-page":"20","volume":"1","author":"K Premalatha","year":"2009","unstructured":"Premalatha K, Natarajan A (2009) Discrete PSO with GA operators for document clustering. Int J Recent Trends Eng 1(1):20\u201324","journal-title":"Int J Recent Trends Eng"},{"issue":"3","key":"9681_CR38","first-page":"302","volume":"2","author":"K Premalatha","year":"2010","unstructured":"Premalatha K, Natarajan AM (2010) Hybrid PSO and GA models for document clustering. Int J Adv Soft Comput Its Appl 2(3):302\u2013320","journal-title":"Int J Adv Soft Comput Its Appl"},{"key":"9681_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.06.015","author":"K Ravi","year":"2015","unstructured":"Ravi K, Ravi V (2015) A survey on opinion mining and sentiment analysis: tasks, approaches and applications. Knowl Based Syst. \n                  https:\/\/doi.org\/10.1016\/j.knosys.2015.06.015","journal-title":"Knowl Based Syst"},{"issue":"25","key":"9681_CR40","first-page":"38","volume":"65","author":"S Sarkar","year":"2013","unstructured":"Sarkar S, Roy A, Purkayastha B (2013) Application of particle swarm optimization in data clustering: a survey. Int J Comput Appl 65(25):38\u201346","journal-title":"Int J Comput Appl"},{"issue":"3","key":"9681_CR41","first-page":"4175","volume":"5","author":"S Sarkar","year":"2014","unstructured":"Sarkar S, Roy A, Purkayastha B (2014a) Clustering of documents using particle swarm optimization and semantics information. Int J Comput Sci Inf Technol 5(3):4175\u20134180","journal-title":"Int J Comput Sci Inf Technol"},{"issue":"3","key":"9681_CR42","doi-asserted-by":"publisher","first-page":"83","DOI":"10.5121\/ijnlc.2014.3308","volume":"3","author":"S Sarkar","year":"2014","unstructured":"Sarkar S, Roy A, Purkayastha BS (2014b) A comparative analysis of particle swarm optimization and K-means algorithm for text clustering using Nepali Wordnet. Int J Nat Lang Comput (IJNLC) 3(3):83\u201392","journal-title":"Int J Nat Lang Comput (IJNLC)"},{"key":"9681_CR43","doi-asserted-by":"crossref","unstructured":"Souza E, Alves T, Teles I, Oliveira ALI, Gusm\u00e3o C (2016a) TOPIE: an open-source opinion mining pipeline to analyze consumers sentiment in Brazilian Portuguese. In: Computational processing of the Portuguese language: 12th international conference, PROPOR 2016, Tomar, Portugal, July 13\u201315, 2016, Proceedings. Springer International Publishing, pp 95\u2013105","DOI":"10.1007\/978-3-319-41552-9_9"},{"key":"9681_CR44","doi-asserted-by":"publisher","unstructured":"Souza E, Oliveira ALI, Silva A, Oliveira G, Santos D (2016b) An unsupervised particle swarm optimization approach for opinion clustering. In: Brazilian conference on intelligent systems, pp 307\u2013312. \n                  https:\/\/doi.org\/10.1109\/BRACIS.2016.54","DOI":"10.1109\/BRACIS.2016.54"},{"key":"9681_CR45","unstructured":"Teles V, Santos D, Souza E (2016) Uma An\u00e1lise Comparativa de T\u00e9cnicas Supervisionadas para Minera\u00e7\u00e3o de Opini\u00e3o de Consumidores Brasileiros no Twitter. In: XIII Encontro Nacional de Intelig\u00eancia Artificial e Computacional (ENIAC-2016), pp 217\u2013228"},{"key":"9681_CR46","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.eswa.2016.03.028","volume":"57","author":"A Tripathy","year":"2016","unstructured":"Tripathy A, Agrawal A, Rath SK (2016) Classification of sentiment reviews using n-gram machine learning approach. Expert Syst Appl 57:117\u2013126","journal-title":"Expert Syst Appl"},{"key":"9681_CR47","unstructured":"Wu ST, Li Y, Xu Y, Pham B, Chen P (2004) Automatic pattern-taxonomy extraction for web mining. In: IEEE\/WIC\/ACM international conference on web intelligence, 2004. WI 2004. Proceedings. IEEE, pp 242\u2013248"},{"key":"9681_CR48","unstructured":"Yang XS, Deb S (2009) Cuckoo search via l\u00e9vy flights. In: World congress on nature and biologically inspired computing, 2009. NaBIC 2009. IEEE, pp 210\u2013214"},{"key":"9681_CR49","doi-asserted-by":"publisher","unstructured":"Zhang Y, Xiong X, Zhang Q (2013) An improved self-adaptive PSO algorithm with detection function for multimodal function optimization problems. Math Probl Eng 2013(2013):716952. \n                  https:\/\/doi.org\/10.1155\/2013\/716952","DOI":"10.1155\/2013\/716952"}],"container-title":["Natural Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11047-018-9681-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11047-018-9681-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11047-018-9681-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T02:03:24Z","timestamp":1597975404000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11047-018-9681-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,25]]},"references-count":49,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["9681"],"URL":"https:\/\/doi.org\/10.1007\/s11047-018-9681-2","relation":{},"ISSN":["1567-7818","1572-9796"],"issn-type":[{"value":"1567-7818","type":"print"},{"value":"1572-9796","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,25]]},"assertion":[{"value":"25 April 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}