{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:50:48Z","timestamp":1743043848691,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":16,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783662493892"},{"type":"electronic","value":"9783662493908"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-662-49390-8_10","type":"book-chapter","created":{"date-parts":[[2016,3,7]],"date-time":"2016-03-07T18:17:15Z","timestamp":1457374635000},"page":"108-116","source":"Crossref","is-referenced-by-count":2,"title":["Fast and Accurate - Improving Lexicon-Based Sentiment Classification with an Ensemble Methods"],"prefix":"10.1007","author":[{"given":"\u0141ukasz","family":"Augustyniak","sequence":"first","affiliation":[]},{"given":"Piotr","family":"Szyma\u0144ski","sequence":"additional","affiliation":[]},{"given":"Tomasz","family":"Kajdanowicz","sequence":"additional","affiliation":[]},{"given":"Przemys\u0142aw","family":"Kazienko","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Augustyniak, L., Kajdanowicz, T., Szymanski, P., Tuliglowicz, W., Kazienko, P., Alhajj, R., Szymanski, B.K.: Simpler is better? lexicon-based ensemble sentiment classification beats supervised methods. In: 2014 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014, Beijing, China, 17\u201320 August 2014, pp. 924\u2013929 (2014)","DOI":"10.1109\/ASONAM.2014.6921696"},{"issue":"1","key":"10_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jocs.2010.12.007","volume":"2","author":"J Bollen","year":"2011","unstructured":"Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. J. Comput. Sci. 2(1), 1\u20138 (2011)","journal-title":"J. Comput. Sci."},{"key":"10_CR3","unstructured":"Brody, S., Elhadad, N.: An unsupervised aspect-sentiment model for online reviews. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, HLT 2010, Stroudsburg, PA, USA, pp. 804\u2013812. Association for Computational Linguistics (2010)"},{"key":"10_CR4","unstructured":"Freund, Y., Schapire, R.E.: Experiments with a new boosting algorithm (1996)"},{"key":"10_CR5","unstructured":"Galitsky, B., McKenna, E.W.: Sentiment extraction from consumer reviews for providing product recommendations, November 12 2009. US Patent App. 12\/119,465"},{"issue":"16","key":"10_CR6","doi-asserted-by":"publisher","first-page":"6266","DOI":"10.1016\/j.eswa.2013.05.057","volume":"40","author":"M Ghiassi","year":"2013","unstructured":"Ghiassi, M., Skinner, J., Zimbra, D.: Twitter brand sentiment analysis: a hybrid system using n-gram analysis and dynamic artificial neural network. Expert Syst. Appl. 40(16), 6266\u20136282 (2013)","journal-title":"Expert Syst. Appl."},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Hassan, A., Abbasi, A., Zeng, D.: Twitter sentiment analysis: a bootstrap ensemble framework. In: 2013 International Conference on Social Computing (SocialCom), pp. 357\u2013364, September 2013","DOI":"10.1109\/SocialCom.2013.56"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2004, pp. 168\u2013177. ACM, New York (2004)","DOI":"10.1145\/1014052.1014073"},{"key":"10_CR9","doi-asserted-by":"crossref","unstructured":"Lin, J., Kolcz, A.: Large-scale machine learning at twitter. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD 2012, pp. 793\u2013804. ACM, New York (2012)","DOI":"10.1145\/2213836.2213958"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"McAuley, J., Leskovec, J.: Hidden factors, hidden topics: understanding rating dimensions with review text. In: The 7th ACM Conference on Recommender Systems, pp. 165\u2013172. ACM (2013)","DOI":"10.1145\/2507157.2507163"},{"key":"10_CR11","doi-asserted-by":"crossref","unstructured":"Mohammad, S., Dunne, C., Dorr, B.: Generating high-coverage semantic orientation lexicons from overtly marked words, a thesaurus. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, Stroudsburg, PA, USA, vol. 2, pp. 599\u2013608. Association for Computational Linguistics (2009)","DOI":"10.3115\/1699571.1699591"},{"key":"10_CR12","unstructured":"Nielsen, F.\u00c5.: Afinn, March 2011"},{"key":"10_CR13","unstructured":"Rodriguez-Penagos, C., Atserias Batalla, J., Codina-Filb\u00e0, J., Garc\u00eda-Narbona, D., Grivolla, J., Lambert, P., Saur\u00ed, R.: FBM: combining lexicon-based ML and heuristics for social media polarities. In: Second Joint Conference on Lexical and Computational Semantics (*SEM). Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), vol. 2, pp. 483\u2013489, Association for Computational Linguistics, Atlanta (2013). http:\/\/www.aclweb.org\/anthology\/S13-2080"},{"issue":"2","key":"10_CR14","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1162\/COLI_a_00049","volume":"37","author":"M Taboada","year":"2011","unstructured":"Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267\u2013307 (2011)","journal-title":"Comput. Linguist."},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Predicting elections with twitter: what 140 characters reveal about political sentiment. In: ICWSM, vol. 10, pp. 178\u2013185 (2010)","DOI":"10.1609\/icwsm.v4i1.14009"},{"key":"10_CR16","doi-asserted-by":"crossref","unstructured":"Whitehead, M., Yaeger, L.: Sentiment mining using ensemble classification models. In: SCSS (1), pp. 509\u2013514. Springer (2008)","DOI":"10.1007\/978-90-481-3658-2_89"}],"container-title":["Lecture Notes in Computer Science","Intelligent Information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-662-49390-8_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T12:52:38Z","timestamp":1720788758000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-662-49390-8_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783662493892","9783662493908"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-662-49390-8_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]}}}