{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T04:33:21Z","timestamp":1749184401301,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819755806"},{"type":"electronic","value":"9789819755813"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5581-3_28","type":"book-chapter","created":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T19:02:53Z","timestamp":1722538973000},"page":"343-355","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BotScout: A Social Bot Detection Algorithm Based on Semantics, Attributes and Neighborhoods"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5929-5948","authenticated-orcid":false,"given":"Hong","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0152-5615","authenticated-orcid":false,"given":"Nuo","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4749-3060","authenticated-orcid":false,"given":"Yang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6482-2535","authenticated-orcid":false,"given":"Xiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0936-5471","authenticated-orcid":false,"given":"Cong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,1]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1038\/s41562-023-01582-0","volume":"7","author":"WJ Brady","year":"2023","unstructured":"Brady, W.J., McLoughlin, K.L., Torres, M.P., et al.: Overperception of moral outrage in online social networks inflates beliefs about intergroup hostility. Nat. Hum. Behav. 7, 917\u2013927 (2023)","journal-title":"Nat. Hum. Behav."},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Pfeffer, J., Matter, D., Sargsyan, A.: The half-life of a Tweet. In: Proceedings of the International AAAI Conference on Web and Social Media, pp. 1163\u20131167 (2023)","DOI":"10.1609\/icwsm.v17i1.22228"},{"issue":"10","key":"28_CR3","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1145\/3409116","volume":"63","author":"S Cresci","year":"2020","unstructured":"Cresci, S.: A decade of social bot detection. Commun. ACM 63(10), 72\u201383 (2020)","journal-title":"Commun. ACM"},{"key":"28_CR4","doi-asserted-by":"publisher","first-page":"115742","DOI":"10.1016\/j.eswa.2021.115742","volume":"186","author":"S Rao","year":"2021","unstructured":"Rao, S., Verma, A.K., Bhatia, T.: A review on social spam detection: challenges, open issues, and future directions. Expert Syst. Appl. 186, 115742 (2021)","journal-title":"Expert Syst. Appl."},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Gopal, M.K., Asha, V., Saju, B., et al.: Tool to detect fake accounts in Twitter. In: 6th International Conference on Intelligent Computing, pp. 165\u2013171 (2023)","DOI":"10.2991\/978-94-6463-250-7_29"},{"key":"28_CR6","doi-asserted-by":"crossref","unstructured":"Chen, W., Pacheco, D., Yang, K.C., et al.: Neutral bots probe political bias on social media. Nat. Commun. 12(1), 5580 (2021)","DOI":"10.1038\/s41467-021-25738-6"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Yang, K.C., Varol, O., Hui, P.M., et al.: Scalable and generalizable social bot detection through data selection. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence, pp. 1096\u20131103 (2020)","DOI":"10.1609\/aaai.v34i01.5460"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Alhosseini, S.A., Tareaf, R.B., Najafi, P., et al.: Detect me if you can: spam bot detection using inductive representation learning. In: Proceedings of the World Wide Web Conference, pp. 148\u2013153 (2019)","DOI":"10.1145\/3308560.3316504"},{"key":"28_CR9","doi-asserted-by":"crossref","unstructured":"Yang, Y., Yang, R., Li, Y., et al.: RoSGAS: adaptive social bot detection with reinforced self-supervised GNN architecture search. ACM Trans. Web 17(3), 1\u201331 (2023)","DOI":"10.1145\/3572403"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Feng, S., Wan, H., Wang, N., et al.: BotRGCN: Twitter bot detection with relational graph convolutional networks. In: Proceedings of the 2021 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 236\u2013239 (2021)","DOI":"10.1145\/3487351.3488336"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Wu, B., Liu, L., Yang, Y., et al.: Using improved conditional generative adversarial networks to detect social bots on Twitter. IEEE Access 8, 36664\u201336680 (2020)","DOI":"10.1109\/ACCESS.2020.2975630"},{"key":"28_CR12","unstructured":"Lin, H., Chen, N., Chen, Y., et al.: BotScan: an unsupervised bot detection based on adversarial learning and social perception. In: Proceedings of the 14th Asian Control Conference (2024)"},{"key":"28_CR13","unstructured":"Zhang, J., Zhang, H., Xia, C., et al.: Graph-BERT: only attention is needed for learning graph representations. arXiv preprint arXiv:2001.05140 (2020)"},{"key":"28_CR14","unstructured":"Liu, Y., Ott, M., Goyal, N., et al.: RoBERTa: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"28_CR15","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., et al.: Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 6000\u20136010 (2017)"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Grover, A., Leskovec, J.: Node2Vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 855\u2013864 (2016)","DOI":"10.1145\/2939672.2939754"},{"issue":"1","key":"28_CR17","doi-asserted-by":"publisher","first-page":"5663","DOI":"10.1038\/s41598-023-31612-w","volume":"13","author":"K Jha","year":"2023","unstructured":"Jha, K., Karmakar, S., Saha, S.: Graph-BERT and language model-based framework for protein-protein interaction identification. Sci. Rep. 13(1), 5663 (2023)","journal-title":"Sci. Rep."},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Morris, C., Ritzert, M., Fey, M., et al.: Weisfeiler and Leman go neural: higher-order graph neural networks. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence, pp. 4602\u20134609 (2019)","DOI":"10.1609\/aaai.v33i01.33014602"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Liu, S., Johns, E.J., Davison, A.J.: End-to-end multi-task learning with attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1871\u20131880 (2019)","DOI":"10.1109\/CVPR.2019.00197"},{"key":"28_CR20","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., Astels, S., et al.: HDBSCAN: hierarchical density based clustering. J. Open Source Softw. 2(11), 205 (2017)","DOI":"10.21105\/joss.00205"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Cresci, S., Di Pietro, R., Petrocchi, M., et al.: Fame for sale: efficient detection of fake Twitter followers. Decis. Support Syst. 80, 56\u201371 (2015)","DOI":"10.1016\/j.dss.2015.09.003"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Feng, S., Wan, H., Wang, N., et al.: TwiBot-20: a comprehensive Twitter bot detection benchmark. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 4485\u20134494 (2021)","DOI":"10.1145\/3459637.3482019"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Hayawi, K., Mathew, S., Venugopal, N., et al.: DeeProBot: a hybrid deep neural network model for social bot detection based on user profile data. Soc. Netw. Anal. Mining 12(1), 43 (2022)","DOI":"10.1007\/s13278-022-00869-w"},{"key":"28_CR24","doi-asserted-by":"crossref","unstructured":"Wei, F., Nguyen, U.T.: Twitter bot detection using bidirectional long short-term memory neural networks and word embeddings. In: Proceedings of the 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, pp. 101\u2013109 (2019)","DOI":"10.1109\/TPS-ISA48467.2019.00021"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Guo, Q.L., Xie, H.Y., Li, Y.Y., et al.: Social bots detection via fusing BERT and graph convolutional networks. Symmetry 14(1), 30 (2022)","DOI":"10.3390\/sym14010030"},{"key":"28_CR26","doi-asserted-by":"crossref","unstructured":"Echeverria, J., De Cristofaro, E., Kourtellis, N., et al.: LOBO - evaluation of generalization deficiencies in Twitter bot classifiers. In: Proceedings of the 34th Annual Computer Security Applications Conference, pp. 137\u2013146 (2018)","DOI":"10.1145\/3274694.3274738"},{"issue":"2","key":"28_CR27","doi-asserted-by":"publisher","first-page":"1516","DOI":"10.1109\/TDSC.2022.3159007","volume":"20","author":"SH Moghaddam","year":"2022","unstructured":"Moghaddam, S.H., Abbaspour, M.: Friendship preference: scalable and robust category of features for social bot detection. IEEE Trans. Dependable Secure Comput. 20(2), 1516\u20131528 (2022)","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"28_CR28","doi-asserted-by":"crossref","unstructured":"Knauth, J.: Language-agnostic Twitter-bot detection. In: Proceedings of the International Conference on Recent Advances in Natural Language Processing, pp. 550\u2013558 (2019)","DOI":"10.26615\/978-954-452-056-4_065"},{"key":"28_CR29","doi-asserted-by":"crossref","unstructured":"Feng, S., Wan, H., Wang, N., et al.: SATAR: a self-supervised approach to Twitter account representation learning and its application in bot detection. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp. 3808\u20133817 (2021)","DOI":"10.1145\/3459637.3481949"},{"key":"28_CR30","unstructured":"Velickovic, P., Cucurull, G., Casanova, A., et al.: Graph attention networks. In: Proceedings of the International Conference on Learning Representations, pp. 1050\u20131062 (2018)"},{"key":"28_CR31","doi-asserted-by":"crossref","unstructured":"Lv, Q.S., Ding, M., Liu, Q., et al.: Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks. In: Proceeding of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1150\u20131160 (2021)","DOI":"10.1145\/3447548.3467350"},{"key":"28_CR32","doi-asserted-by":"crossref","unstructured":"Ng, L.H.X., Carley, K.M.: BotBuster: multi-platform bot detection using a mixture of experts. In: Proceedings of the International AAAI Conference on Web and Social Media, pp. 686\u2013697 (2023)","DOI":"10.1609\/icwsm.v17i1.22179"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5581-3_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T19:16:36Z","timestamp":1722539796000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5581-3_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819755806","9789819755813"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5581-3_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"1 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}