{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T02:12:58Z","timestamp":1772676778338,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2014,10,2]],"date-time":"2014-10-02T00:00:00Z","timestamp":1412208000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2016,2]]},"DOI":"10.1007\/s11042-014-2270-1","type":"journal-article","created":{"date-parts":[[2014,10,1]],"date-time":"2014-10-01T08:59:28Z","timestamp":1412153968000},"page":"1509-1528","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Predicting movie Box-office revenues by exploiting large-scale social media content"],"prefix":"10.1007","volume":"75","author":[{"given":"Ting","family":"Liu","sequence":"first","affiliation":[]},{"given":"Xiao","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Yiheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Haochen","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Maosheng","family":"Guo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2014,10,2]]},"reference":[{"key":"2270_CR1","first-page":"492","volume":"1","author":"S Asur","year":"2010","unstructured":"Asur S, Huberman BA (2010) Predicting the future with social media [C]\/\/Web intelligence and intelligent agent technology (WI-IAT), 2010. IEEE\/WIC\/ACM international conference on IEEE 1:492\u2013499","journal-title":"IEEE\/WIC\/ACM international conference on IEEE"},{"issue":"1","key":"2270_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 (2011) Twitter mood predicts the stock market [J]. J Comput Sci 2(1):1\u20138","journal-title":"J Comput Sci"},{"key":"2270_CR3","unstructured":"Boser B E, Guyon I M, Vapnik V N. (1992) A training algorithm for optimal margin classifiers [C]\/\/ Proceedings of the fifth annual workshop on Computational learning theory. ACM, 144\u2013152"},{"key":"2270_CR4","doi-asserted-by":"crossref","unstructured":"Bothos E., Apostolou D., Mentzas G. (2010) Using Social Media to Predict Future Events with Agent-Based Markets. IEEE Intelligent Systems, vol. PP, no. 99.","DOI":"10.1109\/MIS.2010.152"},{"key":"2270_CR5","unstructured":"Chaovalit P, Zhou L. (2005) Movie review mining: A comparison between supervised and unsupervised classification approaches [C]\/\/System Sciences, 2005. HICSS\u201905. Proceedings of the 38th Annual Hawaii International Conference on. IEEE 112c-112c"},{"key":"2270_CR6","volume-title":"Forecasting gross revenues at the movie box office [J]","author":"A Chen","year":"2002","unstructured":"Chen A (2002) Forecasting gross revenues at the movie box office [J]. University of Washington, Seattle"},{"issue":"1","key":"2270_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37\u201346","journal-title":"Educ Psychol Meas"},{"key":"2270_CR8","unstructured":"Ding X, Liu B, Yu P S. (2008) A holistic lexicon-based approach to opinion mining [C]\/\/Proceedings of the 2008 International Conference on Web Search and Data Mining. ACM, 231\u2013240."},{"key":"2270_CR9","first-page":"155","volume":"9","author":"H Drucker","year":"1997","unstructured":"Drucker H, Burges CJC, Kaufman L et al (1997) Support vector regression machines. J Adv neural inf Process Syst 9:155\u2013161","journal-title":"J Adv neural inf Process Syst"},{"issue":"1","key":"2270_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i01","volume":"33","author":"J Friedman","year":"2010","unstructured":"Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent [J]. J Stat Softw 33(1):1","journal-title":"J Stat Softw"},{"key":"2270_CR11","unstructured":"Gayo-Avello D, Metaxas P T, Mustafaraj E. (2011). Limits of electoral predictions using twitter [C]\/\/ICWSM."},{"key":"2270_CR12","unstructured":"Gruhl D, Guha R, Kumar R, et al. (2005) The predictive power of online chatter [C]\/\/Proceedings of the eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining. ACM, 78\u201387"},{"key":"2270_CR13","doi-asserted-by":"crossref","unstructured":"Jansen H J, Koop R. (2006) Pundits, ideologues, and the ranters: The British Columbia election online [J]. Canadian Journal of Communication, 30 (4)","DOI":"10.22230\/cjc.2005v30n4a1483"},{"issue":"11","key":"2270_CR14","doi-asserted-by":"publisher","first-page":"2169","DOI":"10.1002\/asi.21149","volume":"60","author":"BJ Jansen","year":"2009","unstructured":"Jansen BJ, Zhang M, Sobel K et al (2009) Twitter power: tweets as electronic word of mouth [J]. J Am Soc Inf Sci Technol 60(11):2169\u20132188","journal-title":"J Am Soc Inf Sci Technol"},{"key":"2270_CR15","volume-title":"Making large scale SVM learning practical [J]","author":"T Joachims","year":"1999","unstructured":"Joachims T (1999) Making large scale SVM learning practical [J]"},{"key":"2270_CR16","unstructured":"Joshi M, Das D, Gimpel K, et al. (2010) Movie reviews and revenues: An experiment in text regression [C]\/\/Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 293\u2013296"},{"issue":"2","key":"2270_CR17","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1177\/0894439311404119","volume":"30","author":"A Jungherr","year":"2012","unstructured":"Jungherr A, J\u00fcrgens P, Schoen H (2012) Why the pirate party won the German election of 2009 or the trouble with predictions: a response to tumasjan, a., sprenger, to, sander, pg, & welpe, im \u201cpredicting elections with twitter: what 140 characters reveal about political sentiment\u201d. J Soc Sci Comput Rev 30(2):229\u2013234","journal-title":"J Soc Sci Comput Rev"},{"issue":"2","key":"2270_CR18","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1080\/08997768909358184","volume":"2","author":"BR Litman","year":"1989","unstructured":"Litman BR, Kohl LS (1989) Predicting financial success of motion pictures: The\u201980s experience [J]. J Media Eco 2(2):35\u201350","journal-title":"J Media Eco"},{"issue":"2","key":"2270_CR19","first-page":"46","volume":"15","author":"L Liviu","year":"2011","unstructured":"Liviu L, Mihaela T (2011) Predicting product performance with social media. J Nforma Educ 15(2):46\u201356","journal-title":"J Nforma Educ"},{"key":"2270_CR20","unstructured":"Metaxas P T, Mustafaraj E, Gayo-Avello D. (2011) How (not) to predict elections [C]\/\/Privacy, security, risk and trust (PASSAT), 2011 IEEE third international conference on and 2011 I.E. third international conference on social computing (SocialCom). IEEE, 165\u2013171"},{"key":"2270_CR21","unstructured":"Mishne G, Glance N S. (2006) Predicting Movie Sales from Blogger Sentiment [C]\/\/AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs. 155\u2013158."},{"key":"2270_CR22","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1609\/icwsm.v4i1.14031","volume":"11","author":"B O\u2019Connor","year":"2010","unstructured":"O\u2019Connor B, Balasubramanyan R, Routledge BR et al (2010) From tweets to polls: linking text sentiment to public opinion time series. J ICWSM 11:122\u2013129","journal-title":"J ICWSM"},{"issue":"1\u20132","key":"2270_CR23","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 [J]. Found trends Inf Retr 2(1\u20132):1\u2013135","journal-title":"Found trends Inf Retr"},{"key":"2270_CR24","doi-asserted-by":"crossref","unstructured":"Pang B, Lee L, Vaithyanathan S. (2002) Thumbs up?: sentiment classification using machine learning techniques [C]\/\/Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics 79\u201386","DOI":"10.3115\/1118693.1118704"},{"key":"2270_CR25","unstructured":"Ritterman J, Osborne M, Klein E. (2009) Using prediction markets and Twitter to predict a swine flu pandemic [C]\/\/1st international workshop on mining social media. 9"},{"key":"2270_CR26","doi-asserted-by":"crossref","unstructured":"Sakaki T, Okazaki M, Matsuo Y. (2010) Earthquake shakes Twitter users: real-time event detection by social sensors [C]\/\/Proceedings of the 19th international conference on World Wide Web. ACM, 851\u2013860","DOI":"10.1145\/1772690.1772777"},{"issue":"2","key":"2270_CR27","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1287\/mksc.15.2.113","volume":"15","author":"MS Sawhney","year":"1996","unstructured":"Sawhney MS, Eliashberg J (1996) A parsimonious model for forecasting gross box-office revenues of motion pictures [J]. Mark Sci 15(2):113\u2013131","journal-title":"Mark Sci"},{"key":"2270_CR28","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf B, Smola A J. (2002) Learning with kernels: support vector machines, regularization, optimization, and beyond [M]. MIT press","DOI":"10.7551\/mitpress\/4175.001.0001"},{"issue":"2","key":"2270_CR29","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.eswa.2005.07.018","volume":"30","author":"R Sharda","year":"2006","unstructured":"Sharda R, Delen D (2006) Predicting box-office success of motion pictures with neural networks [J]. Expert Syst Appl 30(2):243\u2013254","journal-title":"Expert Syst Appl"},{"key":"2270_CR30","unstructured":"Sharda R, Meany E. (2000) Forecasting gate receipts using neural network and rough sets [C]\/\/Proceedings of the International DSI Conference. : 1\u20135"},{"key":"2270_CR31","unstructured":"Si J., Mukherjee A., Liu B., Li Q., Li H., Deng X. (2008). Exploiting Topic based Twitter Sentiment for Stock Prediction. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2013), pp. 24\u201329"},{"issue":"3","key":"2270_CR32","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1080\/09332480.2000.10542216","volume":"13","author":"JS Simonoff","year":"2000","unstructured":"Simonoff JS, Sparrow IR (2000) Predicting movie grosses: winners and losers, blockbusters and sleepers [J]. Chance 13(3):15\u201324","journal-title":"Chance"},{"key":"2270_CR33","unstructured":"Skoric M, Poor N, Achananuparp P, et al. (2012) Tweets and votes: A study of the 2011 singapore general election [C]\/\/System Science (HICSS), 2012 45th Hawaii International Conference on. IEEE, 2583\u20132591"},{"issue":"4","key":"2270_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1207\/s15327736me0704_1","volume":"7","author":"S Sochay","year":"1994","unstructured":"Sochay S (1994) Predicting the performance of motion pictures [J]. J Media Eco 7(4):1\u201320","journal-title":"J Media Eco"},{"key":"2270_CR35","unstructured":"Sysomos Inc, \u201cAn In-Depth Look Inside the Twitter World \u201d. http:\/\/www.sysomos.com\/insidetwitter\/ . [Accessed Feb 3, 2012]."},{"key":"2270_CR36","volume-title":"Economic forecasts and policy [J]","author":"H Theil","year":"1961","unstructured":"Theil H (1961) Economic forecasts and policy [J]"},{"key":"2270_CR37","doi-asserted-by":"crossref","unstructured":"Tumasjan A, Sprenger T O, Sandner P G, et al. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment[J]. ICWSM, 2010, 10: 178\u2013185","DOI":"10.1609\/icwsm.v4i1.14009"},{"key":"2270_CR38","unstructured":"UzZaman N, Blanco R, Matthews M. (2012) TwitterPaul: Extracting and Aggregating Twitter Predictions [J]. arXiv preprint arXiv:1211.6496"},{"key":"2270_CR39","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/978-1-4757-3264-1_8","volume-title":"The Nature of Statistical Learning Theory","author":"Vladimir N. Vapnik","year":"2000","unstructured":"Vapnik V. (2000) The nature of statistical learning theory [M]. springer"},{"key":"2270_CR40","unstructured":"Wikipedia, \u201csocial media\u201d. http:\/\/en.wikipedia.org\/wiki\/Social_media"},{"key":"2270_CR41","unstructured":"Williams C, Gulati G. (2008) What is a social network worth? Facebook and vote share in the 2008 presidential primaries[C]. American Political Science Association"},{"issue":"3","key":"2270_CR42","doi-asserted-by":"publisher","first-page":"6580","DOI":"10.1016\/j.eswa.2008.07.064","volume":"36","author":"L Zhang","year":"2009","unstructured":"Zhang L, Luo J, Yang S (2009) Forecasting box office revenue of movies with BP neural network [J]. Expert Syst Appl 36(3):6580\u20136587","journal-title":"Expert Syst Appl"},{"key":"2270_CR43","unstructured":"Zhang W, Skiena S. (2009) Improving movie gross prediction through news analysis [C]\/\/Proceedings of the 2009 IEEE\/WIC\/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 01. IEEE Computer Society 301\u2013304"},{"issue":"2","key":"2270_CR44","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou H, Hastie T (2005) Regularization and variable selection via the elastic net [J]. J R Stat Soc Ser B (Stat Methodol) 67(2):301\u2013320","journal-title":"J R Stat Soc Ser B (Stat Methodol)"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-014-2270-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-014-2270-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-014-2270-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-014-2270-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T23:12:44Z","timestamp":1746400364000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-014-2270-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,10,2]]},"references-count":44,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,2]]}},"alternative-id":["2270"],"URL":"https:\/\/doi.org\/10.1007\/s11042-014-2270-1","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,10,2]]}}}