{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T13:09:16Z","timestamp":1726060156423},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030349851"},{"type":"electronic","value":"9783030349868"}],"license":[{"start":{"date-parts":[[2019,11,28]],"date-time":"2019-11-28T00:00:00Z","timestamp":1574899200000},"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":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-34986-8_18","type":"book-chapter","created":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T10:02:47Z","timestamp":1574848967000},"page":"248-262","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Study of Predicting Social Topic Trends"],"prefix":"10.1007","author":[{"given":"Sung-Shun","family":"Weng","sequence":"first","affiliation":[]},{"given":"Huai-Wen","family":"Hsu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,11,28]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Chen, Y., Amiri, H., Li, Z., Chua, T.-S.: Emerging topic detection for organizations from microblogs. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 43\u201352. ACM, New York (2013)","DOI":"10.1145\/2484028.2484057"},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Ritter, A., Etzioni, O., Clark, S.: Open domain event extraction from Twitter. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1104\u20131112. ACM, New York (2012)","DOI":"10.1145\/2339530.2339704"},{"issue":"1","key":"18_CR3","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.bushor.2009.09.003","volume":"53","author":"AM Kaplan","year":"2010","unstructured":"Kaplan, A.M., Haenlein, M.: Users of the world, unite! the challenges and opportunities of Social Media. Bus. Horiz. 53(1), 59\u201368 (2010)","journal-title":"Bus. Horiz."},{"key":"18_CR4","volume-title":"Introduction to Electronic Commerce","author":"E Turban","year":"2009","unstructured":"Turban, E., King, D.R., Lang, J.: Introduction to Electronic Commerce. Prentice Hall, Upper Saddle River (2009)"},{"key":"18_CR5","volume-title":"Marketing Management","author":"P Kotler","year":"2009","unstructured":"Kotler, P., Keller, K.L.: Marketing Management. Pearson Prentice Hall, Upper Saddle River (2009)"},{"key":"18_CR6","volume-title":"The Social Media Management Handbook: Everything You Need to Know to Get Social Media Working in Your Business","author":"N Smith","year":"2011","unstructured":"Smith, N., Wollan, R., Zhou, C.: The Social Media Management Handbook: Everything You Need to Know to Get Social Media Working in Your Business. Wiley, Hoboken (2011)"},{"key":"18_CR7","volume-title":"Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World","author":"C Hemann","year":"2013","unstructured":"Hemann, C., Burbary, K.: Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World. Que, Indianapolis (2013)"},{"key":"18_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19460-3","volume-title":"Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data","author":"B Liu","year":"2011","unstructured":"Liu, B.: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer, Berlin (2011)"},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"Cha, M., Haddadi, H., Benevenuto, F., Gummadi, P.K.: Measuring user influence in Twitter: the million follower fallacy. In: ICWSM, vol. 10, no. 10-17, p. 30 (2010)","DOI":"10.1609\/icwsm.v4i1.14033"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Li, H., Mukherjee, A., Liu, B., Kornfield, R., Emery, S.: Detecting campaign promoters on Twitter using markov random fields. In: 2014 IEEE International Conference on Data Mining, pp. 290\u2013299 (2014)","DOI":"10.1109\/ICDM.2014.59"},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Singh, V.K., Piryani, R., Uddin, A., Waila, P.: Sentiment analysis of movie reviews and blog posts. In: 2013 IEEE 3rd International Advance Computing Conference (IACC), pp. 893\u2013898 (2013)","DOI":"10.1109\/IAdCC.2013.6514345"},{"key":"18_CR12","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/978-3-540-39857-8_7","volume-title":"Machine Learning: ECML 2003","author":"CC Chen","year":"2003","unstructured":"Chen, C.C., Chen, Y.-T., Sun, Y., Chen, M.C.: Life cycle modeling of news events using aging theory. In: Lavra\u010d, N., Gamberger, D., Blockeel, H., Todorovski, L. (eds.) Machine Learning: ECML 2003, pp. 47\u201359. Springer, Berlin Heidelberg (2003)"},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Sayyadi, H., Hurst, M., Maykov, A.: Event detection and tracking in social streams. In: ICWSM, May 2009","DOI":"10.1609\/icwsm.v3i1.13970"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Cataldi, M., Di Caro, L., Schifanella, C.: Emerging topic detection on Twitter based on temporal and social terms evaluation. In: Proceedings of the Tenth International Workshop on Multimedia Data Mining, pp. 4:1\u20134:10. ACM, New York (2010)","DOI":"10.1145\/1814245.1814249"},{"key":"18_CR15","first-page":"139","volume-title":"Natural Language Processing \u2013 IJCNLP 2004","author":"L You","year":"2004","unstructured":"You, L., Du, Y., Ge, J., Huang, X., Wu, L.: BBS based hot topic retrieval using back-propagation neural network. In: Su, K.-Y., Tsujii, J., Lee, J.-H., Kwong, O.Y. (eds.) Natural Language Processing \u2013 IJCNLP 2004, pp. 139\u2013148. Springer, Berlin Heidelberg (2004)"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Xie, J., Liu, G., Ning, W.: A topic detection method for Chinese microblog. In: 2012 International Symposium on Information Science and Engineering (ISISE), pp. 100\u2013103 (2012)","DOI":"10.1109\/ISISE.2012.30"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"Becker, H., Naaman, M., Gravano, L.: Learning similarity metrics for event identification in social media. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, pp. 291\u2013300. ACM, New York (2010)","DOI":"10.1145\/1718487.1718524"},{"issue":"4","key":"18_CR18","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1145\/2133806.2133826","volume":"55","author":"DM Blei","year":"2012","unstructured":"Blei, D.M.: Probabilistic topic models. Commun. ACM 55(4), 77\u201384 (2012)","journal-title":"Commun. ACM"},{"issue":"1\u20132","key":"18_CR19","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1023\/A:1007617005950","volume":"42","author":"T Hofmann","year":"2001","unstructured":"Hofmann, T.: Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn. 42(1\u20132), 177\u2013196 (2001)","journal-title":"Mach. Learn."},{"key":"18_CR20","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"18_CR21","doi-asserted-by":"crossref","unstructured":"Wang, X., McCallum, A.: Topics over Time: a non-Markov continuous-time model of topical trends. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 424\u2013433. ACM, New York (2006)","DOI":"10.1145\/1150402.1150450"},{"key":"18_CR22","doi-asserted-by":"crossref","unstructured":"Wang, Y., Agichtein, E., Benzi, M.: TM-LDA: efficient online modeling of latent topic transitions in social media. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 123\u2013131. ACM, New York (2012)","DOI":"10.1145\/2339530.2339552"},{"issue":"8","key":"18_CR23","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1145\/1787234.1787254","volume":"53","author":"G Szabo","year":"2010","unstructured":"Szabo, G., Huberman, B.A.: Predicting the popularity of online content. Commun. ACM 53(8), 80\u201388 (2010)","journal-title":"Commun. ACM"},{"key":"18_CR24","doi-asserted-by":"crossref","unstructured":"Achrekar, H., Gandhe, A., Lazarus, R., Yu, S.-H., Liu, B.: Predicting flu trends using twitter data. In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 702\u2013707 (2011)","DOI":"10.1109\/INFCOMW.2011.5928903"},{"key":"18_CR25","doi-asserted-by":"crossref","unstructured":"Kim, S.D., Kim, S.H., Cho, H.G.: Predicting the virtual temperature of web-blog articles as a measurement tool for online popularity. In: 2011 IEEE 11th International Conference on Computer and Information Technology (CIT), pp. 449\u2013454 (2011)","DOI":"10.1109\/CIT.2011.104"},{"key":"18_CR26","unstructured":"Ritterman, J., Osborne, M., Klein, E.: Using prediction markets and Twitter to predict a swine flu pandemic. In: 1st International Workshop on Mining Social Media, vol. 9, pp. 9\u201317, November 2009"},{"key":"18_CR27","unstructured":"Bandari, R., Asur, S., Huberman, B.A.: The pulse of news in social media: forecasting popularity (2012)"},{"issue":"3","key":"18_CR28","doi-asserted-by":"publisher","first-page":"1583","DOI":"10.1214\/14-AOAS741","volume":"8","author":"T Zaman","year":"2014","unstructured":"Zaman, T., Fox, E.B., Bradlow, E.T.: A Bayesian approach for predicting the popularity of tweets. Ann. Appl. Stat. 8(3), 1583\u20131611 (2014)","journal-title":"Ann. Appl. Stat."},{"key":"18_CR29","doi-asserted-by":"crossref","unstructured":"Figueiredo, F.: On the prediction of popularity of trends and hits for user generated videos. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, pp. 741\u2013746. ACM New York (2013)","DOI":"10.1145\/2433396.2433489"},{"key":"18_CR30","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1007\/978-3-319-23485-4_53","volume-title":"Progress in Artificial Intelligence","author":"K Fernandes","year":"2015","unstructured":"Fernandes, K., Vinagre, P., Cortez, P.: A proactive intelligent decision support system for predicting the popularity of online news. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) Progress in Artificial Intelligence, pp. 535\u2013546. Springer, Berlin (2015)"},{"issue":"2","key":"18_CR31","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"LR Rabiner","year":"1989","unstructured":"Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257\u2013286 (1989)","journal-title":"Proc. IEEE"},{"key":"18_CR32","volume-title":"Industrial and Business Forecasting Methods: A Practical Guide to Exponential Smoothing and Curve Fitting","author":"CD Lewis","year":"1982","unstructured":"Lewis, C.D.: Industrial and Business Forecasting Methods: A Practical Guide to Exponential Smoothing and Curve Fitting. Butterworth-Heinemann, Oxford (1982)"},{"issue":"Suppl. 1","key":"18_CR33","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"TL Griffiths","year":"2004","unstructured":"Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Nat. Acad. Sci. 101(Suppl. 1), 5228\u20135235 (2004)","journal-title":"Proc. Nat. Acad. Sci."}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advances in E-Business Engineering for Ubiquitous Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-34986-8_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,23]],"date-time":"2023-09-23T11:12:38Z","timestamp":1695467558000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-34986-8_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,28]]},"ISBN":["9783030349851","9783030349868"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-34986-8_18","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2019,11,28]]},"assertion":[{"value":"28 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICEBE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on e-Business Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icebe2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.computer.org\/icebe\/2019\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}