{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T04:35:33Z","timestamp":1759206933640},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T00:00:00Z","timestamp":1574294400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T00:00:00Z","timestamp":1574294400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Beijing Municipal Social Science Foundation","award":["No.15JDZHC011"],"award-info":[{"award-number":["No.15JDZHC011"]}]},{"name":"the project of Double Top-Class Foundation of BFSU","award":["No.YY19ZZA012"],"award-info":[{"award-number":["No.YY19ZZA012"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1007\/s10844-019-00586-5","type":"journal-article","created":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T07:02:51Z","timestamp":1574319771000},"page":"27-49","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Topic-sentiment evolution over time: a manifold learning-based model for online news"],"prefix":"10.1007","volume":"55","author":[{"given":"Yuemei","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ye","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianqiao","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,21]]},"reference":[{"key":"586_CR1","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1038\/s41562-017-0189-z","volume":"2","author":"DJ Benjamin","year":"2018","unstructured":"Benjamin, D.J., Berger, J.O., Johannesson, M., et al. (2018). Redefine statistical significance. Nature Human Behaviour, 2, 6\u201310.","journal-title":"Nature Human Behaviour"},{"key":"586_CR2","unstructured":"Bing, L., & Lei, Z. (2012). A survey of opinion mining and sentiment analysis. In Mining text data (pp. 415\u2013463): Springer."},{"key":"586_CR3","unstructured":"Bo, P., & Lillian, L. (2008). Opinion mining and sentiment analysis. In Journal of foundations and trends in information retrieval, (Vol. 2 pp. 1\u2013135)."},{"key":"586_CR4","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1016\/j.knosys.2013.06.014","volume":"50","author":"Z Bu","year":"2013","unstructured":"Bu, Z., Zhang, C., Xia, Z., Wang, J. (2013). A fast parallelmodularity optimization algorithm (fpmqa) for community detection in online social network. Knowledge-Based Systems, 50, 246\u2013259.","journal-title":"Knowledge-Based Systems"},{"key":"586_CR5","unstructured":"Dermouche, M., Velcin, J., Khouas, L., Loudcher, S. (2014). A joint model for topic-sentiment evolution over time. In IEEE international conference on data mining (pp. 773\u2013778): IEEE."},{"key":"586_CR6","unstructured":"Gong, C., Tao, D., Liu, W. (2016). Label propagation via teaching-to-learn and learning-to-teach. IEEE Transactions on Neural Networks and Learning Systems, 1452\u20131465."},{"key":"586_CR7","unstructured":"Hoffman, M., Bach, F.R., Blei, D.M. (2010). Online learning for latent dirichlet allocation. In Proceedings of the neural information processing systems conference (pp. 993\u20131022)."},{"key":"586_CR8","unstructured":"Hofmann, T. (2017). Probabilistic latent semantic indexing. In SIGIR Forum-SIGIR test-of-time awardees 1978-2001 (pp. 211\u2013218): ACM."},{"issue":"1","key":"586_CR9","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1002\/wcs.1203","volume":"4","author":"MC Hout","year":"2013","unstructured":"Hout, M.C., Papesh, M.H., Goldinger, S.D. (2013). Multidimensional scaling. Wires Cognitive Science, 4(1), 93\u2013103.","journal-title":"Wires Cognitive Science"},{"key":"586_CR10","unstructured":"Jo, Y., & Oh, A.H. (2011). Aspect and sentiment unification model for online review analysis. In Proceedings of the fourth ACM international conference on Web search and data mining (pp. 815\u2013824). New York: ACM."},{"issue":"7","key":"586_CR11","first-page":"1775","volume":"72","author":"C Juan","year":"2009","unstructured":"Juan, C., Tian, X., Li, J. (2009). A density based method for adaptive lda model selection. Neuro Computing, 72(7), 1775\u20131781.","journal-title":"Neuro Computing"},{"issue":"4","key":"586_CR12","first-page":"4","volume":"28","author":"C Keming","year":"2011","unstructured":"Keming, C., & Fang, L. (2011). Lda model-based news topic evolution. Computer Application and software, 28(4), 4\u20138.","journal-title":"Computer Application and software"},{"key":"586_CR13","doi-asserted-by":"crossref","unstructured":"Li, F., Huang, M., Zhu, X. (2010). Sentiment analysis with global topics and local dependency. In Proceedings of the twenty-fourth AAAI conference on artificial intelligence. Association for the Advancement of Artificial Intelligence (pp. 1371\u20131376).","DOI":"10.1609\/aaai.v24i1.7523"},{"key":"586_CR14","doi-asserted-by":"crossref","unstructured":"Lin, C., & He, Y. (2009). Joint sentiment\/topic model for sentiment analysis. In Proceedings of the 18th ACM conference on Information and knowledge management (pp. 375\u2013384).","DOI":"10.1145\/1645953.1646003"},{"key":"586_CR15","unstructured":"Lin, C., He, Y., Everson, R., Ruger, S. (2012). Weakly supervised joint sentiment-topic detection from text. In IEEE transactions on knowledge and data engineering, (Vol. 24 pp. 424\u2013433): IEEE."},{"key":"586_CR16","doi-asserted-by":"crossref","unstructured":"Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 1\u2013143.","DOI":"10.2200\/S00416ED1V01Y201204HLT016"},{"key":"586_CR17","unstructured":"Mei, Q., Ling, X., Wondra, M., Su, H., Zhai, C.X. (2007). Topic sentiment mixture: modeling facets and opinions in weblogs. In Proceedings of the 16th international conference on World Wide Web (pp. 171\u2013180). New York: ACM."},{"issue":"1","key":"586_CR18","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1109\/TIFS.2015.2442527","volume":"11","author":"MA Oikawa","year":"2016","unstructured":"Oikawa, M.A., Dias, Z., de Rezende Rocha, A. (2016). Manifold learning and spectral clustering for image phylogeny forests. IEEE Transactions on Information Forenstcs and Security, 11(1), 5\u201319.","journal-title":"IEEE Transactions on Information Forenstcs and Security"},{"issue":"5500","key":"586_CR19","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis, S.T., & Saul, L.K. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500), 2323\u20132326.","journal-title":"Science"},{"issue":"3","key":"586_CR20","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.pmrj.2014.02.001","volume":"6","author":"KL Sainani","year":"2014","unstructured":"Sainani, K.L. (2014). Introduction to principal components analysis. PMR, 6(3), 275\u2013278.","journal-title":"PMR"},{"issue":"2","key":"586_CR21","first-page":"134","volume":"143","author":"VS Tomar","year":"2014","unstructured":"Tomar, V.S., & Rose, R.C. (2014). Multi-feature multi-manifold learning for single-sample face recognition. Neurocomputing, 143(2), 134\u2013143.","journal-title":"Neurocomputing"},{"key":"586_CR22","doi-asserted-by":"crossref","unstructured":"Wang, X., & McCallum, A. (2006). Topics over time: a non-markov continuous-time model of topical trends. KDD\u201906. Philadelphia, PA, USA, 424\u2013433.","DOI":"10.1145\/1150402.1150450"},{"issue":"6","key":"586_CR23","doi-asserted-by":"publisher","first-page":"7606","DOI":"10.1109\/TNNLS.2015.2477537","volume":"27","author":"Q Wang","year":"2016","unstructured":"Wang, Q., Lin, J., Yuan, Y. (2016). Salient band selection for hyperspectral image classification via manifold ranking. IEEE Transactions on Neural Networks and Learning Systems, 27(6), 7606\u20137618.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"23","key":"586_CR24","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/s10579-005-7880-9","volume":"39","author":"J Wiebe","year":"2005","unstructured":"Wiebe, J., Wilson, T., Cardie, C. (2005). Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(23), 165\u2013210.","journal-title":"Language Resources and Evaluation"},{"key":"586_CR25","unstructured":"Yan, H., Lu, J., Zhou, X. (2013). Efficient manifold learning for speech recognition using locality sensitive hashing. IEEE International Conference on Acoustics, Speech and Signal Processing, 1324\u20131331."},{"issue":"1","key":"586_CR26","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1109\/TSMCB.2012.2202901","volume":"43","author":"Z Zhang","year":"2013","unstructured":"Zhang, Z., Chow, T.W.S., Zhao, M. (2013). M-isomap: orthogonal constrained marginal isomap for nonlinear dimensionality reduction. IEEE Transactions on Cybernetics, 43(1), 180\u2013191.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"586_CR27","unstructured":"Zhu, X., Han, W., Chen, W. (2015). Gridgraph: large-scale graph processing on a single machine using 2-level hierarchical partitioning. In 2015 USENIX annual technical conference. USENIX (pp. 375\u2013386)."}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-019-00586-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10844-019-00586-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-019-00586-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T15:15:41Z","timestamp":1665069341000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10844-019-00586-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,21]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["586"],"URL":"https:\/\/doi.org\/10.1007\/s10844-019-00586-5","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"value":"0925-9902","type":"print"},{"value":"1573-7675","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,21]]},"assertion":[{"value":"23 January 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}