{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:28:47Z","timestamp":1778693327747,"version":"3.51.4"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030908874","type":"print"},{"value":"9783030908881","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-90888-1_28","type":"book-chapter","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T14:13:49Z","timestamp":1638454429000},"page":"370-384","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Event Detection in Social Media via Graph Neural Network"],"prefix":"10.1007","author":[{"given":"Wang","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,1]]},"reference":[{"key":"28_CR1","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. (JMLR) 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res. (JMLR)"},{"key":"28_CR2","doi-asserted-by":"publisher","first-page":"152183","DOI":"10.1109\/ACCESS.2020.3017382","volume":"8","author":"L Cai","year":"2020","unstructured":"Cai, L., Song, Y., Liu, T., Zhang, K.: A hybrid BERT model that incorporates label semantics via adjustive attention for multi-label text classification. IEEE Access 8, 152183\u2013152192 (2020)","journal-title":"IEEE Access"},{"issue":"6","key":"28_CR3","first-page":"1","volume":"9","author":"T Cheng","year":"2014","unstructured":"Cheng, T., Wicks, T.: Event detection using Twitter: a spatio-temporal approach. PLoS ONE 9(6), 1\u201310 (2014)","journal-title":"PLoS ONE"},{"issue":"12","key":"28_CR4","doi-asserted-by":"publisher","first-page":"2928","DOI":"10.1109\/TKDE.2014.2313872","volume":"26","author":"X Cheng","year":"2014","unstructured":"Cheng, X., Yan, X., Lan, Y., Guo, J.: BTM: topic modeling over short texts. IEEE Trans. Knowl. Data Eng. (TKDE) 26(12), 2928\u20132941 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng. (TKDE)"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Cho, K., Merrienboer, B.V., Bahdanau, D., Bengio, Y.: On the properties of neural machine translation: encoder-decoder approaches. In: Proceedings of Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST), pp. 103\u2013111 (2014)","DOI":"10.3115\/v1\/W14-4012"},{"key":"28_CR6","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.neucom.2016.09.127","volume":"254","author":"W Cui","year":"2017","unstructured":"Cui, W., et al.: An algorithm for event detection based on social media data. Neurocomputing 254, 53\u201358 (2017)","journal-title":"Neurocomputing"},{"key":"28_CR7","unstructured":"Defferrard, M., Bresson, X., Vandergheynst, P.: Convolutional neural networks on graphs with fast localized spectral filtering. In: Proceedings of Advances in Neural Information Processing Systems (NeurIPS), pp. 3837\u20133845 (2016)"},{"key":"28_CR8","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), pp. 4171\u20134186 (2019)"},{"issue":"5","key":"28_CR9","doi-asserted-by":"publisher","first-page":"1374","DOI":"10.1007\/s10618-015-0421-2","volume":"29","author":"X Dong","year":"2015","unstructured":"Dong, X., Mavroeidis, D., Calabrese, F., Frossard, P.: Multiscale event detection in social media. Data Min. Knowl. Discov. 29(5), 1374\u20131405 (2015). https:\/\/doi.org\/10.1007\/s10618-015-0421-2","journal-title":"Data Min. Knowl. Discov."},{"issue":"1","key":"28_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13755-019-0084-2","volume":"7","author":"J Du","year":"2019","unstructured":"Du, J., Michalska, S., Subramani, S., Wang, H., Zhang, Y.: Neural attention with character embeddings for hay fever detection from twitter. Health Inf. Sci. Syst. 7(1), 1\u20137 (2019). https:\/\/doi.org\/10.1007\/s13755-019-0084-2","journal-title":"Health Inf. Sci. Syst."},{"issue":"2","key":"28_CR11","doi-asserted-by":"publisher","first-page":"145","DOI":"10.14311\/NNW.2020.30.011","volume":"30","author":"W Gao","year":"2020","unstructured":"Gao, W., Fang, Y., Zhang, F., Yang, Z.: Representation learning of knowledge graphs using convolutional neural networks. Neural Netw. World (NNW) 30(2), 145\u2013160 (2020)","journal-title":"Neural Netw. World (NNW)"},{"issue":"4","key":"28_CR12","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/MMUL.2020.3012675","volume":"27","author":"W Gao","year":"2020","unstructured":"Gao, W., Li, L., Zhu, X., Wang, Y.: Detecting disaster-related tweets via multi-modal adversarial neural network. IEEE Multimedia 27(4), 28\u201337 (2020)","journal-title":"IEEE Multimedia"},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.neucom.2019.11.077","volume":"383","author":"W Gao","year":"2020","unstructured":"Gao, W., et al.: Generation of topic evolution graphs from short text streams. Neurocomputing 383, 282\u2013294 (2020)","journal-title":"Neurocomputing"},{"issue":"2","key":"28_CR14","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1007\/s10115-018-1314-7","volume":"61","author":"W Gao","year":"2018","unstructured":"Gao, W., Peng, M., Wang, H., Zhang, Y., Xie, Q., Tian, G.: Incorporating word embeddings into topic modeling of short text. Knowl. Inf. Syst. 61(2), 1123\u20131145 (2018). https:\/\/doi.org\/10.1007\/s10115-018-1314-7","journal-title":"Knowl. Inf. Syst."},{"key":"28_CR15","unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: Proceedings of International Conference on Machine Learning (ICML), pp. 1263\u20131272 (2017)"},{"issue":"5","key":"28_CR16","doi-asserted-by":"publisher","first-page":"2835","DOI":"10.1007\/s11280-019-00776-9","volume":"23","author":"J He","year":"2020","unstructured":"He, J., Rong, J., Sun, L., Wang, H., Zhang, Y., Ma, J.: A framework for cardiac arrhythmia detection from IoT-based ECGs. World Wide Web 23(5), 2835\u20132850 (2020)","journal-title":"World Wide Web"},{"key":"28_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.engappai.2020.104061","volume":"97","author":"Y Hu","year":"2021","unstructured":"Hu, Y., Zhang, Z., Yao, Y., Huyan, X., Zhou, X., Lee, W.S.: A bidirectional graph neural network for traveling salesman problems on arbitrary symmetric graphs. Eng. Appl. Artif. Intell. 97, 1\u20139 (2021)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"4","key":"28_CR18","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1007\/s10707-016-0263-0","volume":"20","author":"T Hua","year":"2016","unstructured":"Hua, T., Chen, F., Zhao, L., Lu, C.-T., Ramakrishnan, N.: Automatic targeted-domain spatiotemporal event detection in twitter. GeoInformatica 20(4), 765\u2013795 (2016). https:\/\/doi.org\/10.1007\/s10707-016-0263-0","journal-title":"GeoInformatica"},{"issue":"6","key":"28_CR19","doi-asserted-by":"publisher","first-page":"2545","DOI":"10.1007\/s11280-018-0639-1","volume":"22","author":"H Jiang","year":"2018","unstructured":"Jiang, H., Zhou, R., Zhang, L., Wang, H., Zhang, Y.: Sentence level topic models for associated topics extraction. World Wide Web 22(6), 2545\u20132560 (2018). https:\/\/doi.org\/10.1007\/s11280-018-0639-1","journal-title":"World Wide Web"},{"key":"28_CR20","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.jocs.2014.11.004","volume":"6","author":"SB Kaleel","year":"2015","unstructured":"Kaleel, S.B., Abhari, A.: Cluster-discovery of twitter messages for event detection and trending. J. Comput. Sci. (JOCS) 6, 47\u201357 (2015)","journal-title":"J. Comput. Sci. (JOCS)"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of Empirical Methods in Natural Language Processing (EMNLP), pp. 1746\u20131751 (2014)","DOI":"10.3115\/v1\/D14-1181"},{"key":"28_CR22","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. In: Proceedings of International Conference on Learning Representations (ICLR), pp. 1\u201314 (2017)"},{"key":"28_CR23","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.neucom.2019.01.078","volume":"337","author":"G Liu","year":"2019","unstructured":"Liu, G., Guo, J.: Bidirectional LSTM with attention mechanism and convolutional layer for text classification. Neurocomputing 337, 325\u2013338 (2019)","journal-title":"Neurocomputing"},{"key":"28_CR24","unstructured":"Liu, P., Qiu, X., Huang, X.: Recurrent neural network for text classification with multi-task learning. In: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 2873\u20132879 (2016)"},{"key":"28_CR25","unstructured":"Miao, Y., Grefenstette, E., Blunsom, P.: Discovering discrete latent topics with neural variational inference. In: Proceedings of International Conference on Machine Learning (ICML), pp. 2410\u20132419 (2017)"},{"key":"28_CR26","doi-asserted-by":"crossref","unstructured":"Shen, S., et al.: Q-BERT: hessian based ultra low precision quantization of BERT. In: Proceedings of Conference on Artificial Intelligence (AAAI), pp. 8815\u20138821 (2020)","DOI":"10.1609\/aaai.v34i05.6409"},{"key":"28_CR27","doi-asserted-by":"crossref","unstructured":"Shen, Y., Li, H., Yi, S., Chen, D., Wang, X.: Person re-identification with deep similarity-guided graph neural network. In: Proceedings of European Conference on Computer Vision (ECCV), pp. 508\u2013526 (2018)","DOI":"10.1007\/978-3-030-01267-0_30"},{"key":"28_CR28","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.ins.2020.07.036","volume":"544","author":"H Tang","year":"2021","unstructured":"Tang, H., Ji, D., Zhou, Q.: Triple-based graph neural network for encoding event units in graph reasoning problems. Inf. Sci. 544, 168\u2013182 (2021)","journal-title":"Inf. Sci."},{"key":"28_CR29","doi-asserted-by":"publisher","first-page":"8708","DOI":"10.1109\/ACCESS.2021.3049391","volume":"9","author":"X Tian","year":"2021","unstructured":"Tian, X., Wang, J.: Retrieval of scientific documents based on HFS and BERT. IEEE Access 9, 8708\u20138717 (2021)","journal-title":"IEEE Access"},{"issue":"1","key":"28_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3122982","volume":"18","author":"D Wang","year":"2017","unstructured":"Wang, D., Al-Rubaie, A., Clarke, S.S., Davies, J.: Real-time traffic event detection from social media. ACM Trans. Internet Technol. (TOIT) 18(1), 1\u201323 (2017)","journal-title":"ACM Trans. Internet Technol. (TOIT)"},{"issue":"3","key":"28_CR31","doi-asserted-by":"publisher","first-page":"678","DOI":"10.3390\/ijerph17030678","volume":"17","author":"Y Wang","year":"2020","unstructured":"Wang, Y., Xu, K., Kang, Y., Wang, H., Wang, F., Avram, A.: Regional influenza prediction with sampling twitter data and PDE model. Int. J. Environ. Res. Public Health 17(3), 678\u2013680 (2020)","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"28_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/978-3-642-41154-0_4","volume-title":"Web Information Systems Engineering \u2013 WISE 2013","author":"Z Wu","year":"2013","unstructured":"Wu, Z., Yin, W., Cao, J., Xu, G., Cuzzocrea, A.: Community detection in multi-relational social networks. In: Lin, X., Manolopoulos, Y., Srivastava, D., Huang, G. (eds.) WISE 2013. LNCS, vol. 8181, pp. 43\u201356. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-41154-0_4"},{"key":"28_CR33","doi-asserted-by":"crossref","unstructured":"Yao, L., Mao, C., Luo, Y.: Graph convolutional networks for text classification. In: Proceedings of Conference on Artificial Intelligence (AAAI), pp. 7370\u20137377 (2019)","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"28_CR34","unstructured":"Zhang, M., Chen, Y.: Link prediction based on graph neural networks. In: Proceedings of Advances in Neural Information Processing Systems (NeurIPS), pp. 5171\u20135181 (2018)"},{"key":"28_CR35","doi-asserted-by":"crossref","unstructured":"Zhou, W., Ge, T., Xu, K., Wei, F., Zhou, M.: Bert-based lexical substitution. In: Proceedings of Annual Meeting of the Association for Computational Linguistics (ACL), pp. 3368\u20133373 (2019)","DOI":"10.18653\/v1\/P19-1328"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems Engineering \u2013 WISE 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-90888-1_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T14:24:11Z","timestamp":1638455051000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-90888-1_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030908874","9783030908881"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-90888-1_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Melbourne, VIC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wise2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.wise-conferences.org\/2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"229","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"55","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}