{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:05:17Z","timestamp":1750219517425,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819681723","type":"print"},{"value":"9789819681730","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-8173-0_2","type":"book-chapter","created":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T11:42:11Z","timestamp":1750160531000},"page":"16-28","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ComFairGNN: Community Fair Graph Neural Network"],"prefix":"10.1007","author":[{"given":"Yonas","family":"Sium","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3136-2157","authenticated-orcid":false,"given":"Qi","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"2_CR1","unstructured":"Agarwal, C., Lakkaraju, H., Zitnik, M.: Towards a unified framework for fair and stable graph representation learning. In: Uncertainty in Artificial Intelligence, pp. 2114\u20132124. PMLR (2021)"},{"key":"2_CR2","unstructured":"Agarwal, C., Lakkaraju*, H., Zitnik*, M.: Towards a unified framework for fair and stable graph representation learning (2021)"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Bourigault, S., Lagnier, C., Lamprier, S., Denoyer, L., Gallinari, P.: Learning social network embeddings for predicting information diffusion. In: Proceedings of the 7th ACM International Conference on Web Search and Data Mining, pp. 393\u2013402 (2014)","DOI":"10.1145\/2556195.2556216"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Dai, E., Wang, S.: Say no to the discrimination: learning fair graph neural networks with limited sensitive attribute information. In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, pp. 680\u2013688 (2021)","DOI":"10.1145\/3437963.3441752"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Dong, Y., Liu, N., Jalaian, B., Li, J.: Edits: modeling and mitigating data bias for graph neural networks. In: Proceedings of the ACM Web Conference 2022, pp. 1259\u20131269 (2022)","DOI":"10.1145\/3485447.3512173"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Dong, Y., Ma, J., Wang, S., Chen, C., Li, J.: Fairness in graph mining: a survey. IEEE Trans. Knowl. Data Eng. (2023)","DOI":"10.1109\/TKDE.2023.3265598"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Dwork, C., Hardt, M., Pitassi, T., Reingold, O., Zemel, R.: Fairness through awareness. In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 214\u2013226 (2012)","DOI":"10.1145\/2090236.2090255"},{"key":"2_CR8","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"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Guerra, P., Meira\u00a0Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Proceedings of the international AAAI Conference on Web and Social Media, vol.\u00a07, pp. 215\u2013224 (2013)","DOI":"10.1609\/icwsm.v7i1.14421"},{"key":"2_CR10","unstructured":"Hardt, M., Price, E., Srebro, N.: Equality of opportunity in supervised learning. Adv. Neural Inform. Process. Syst. 29 (2016)"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"He, R., McAuley, J.: Ups and downs: modeling the visual evolution of fashion trends with one-class collaborative filtering. In: Proceedings of the 25th International Conference on World Wide Web, pp. 507\u2013517 (2016)","DOI":"10.1145\/2872427.2883037"},{"key":"2_CR12","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Liu, Z., Nguyen, T.K., Fang, Y.: On generalized degree fairness in graph neural networks. arXiv preprint arXiv:2302.03881 (2023)","DOI":"10.1609\/aaai.v37i4.25574"},{"key":"2_CR14","unstructured":"Ma, Y., Liu, X., Shah, N., Tang, J.: Is homophily a necessity for graph neural networks? arXiv preprint arXiv:2106.06134 (2021)"},{"key":"2_CR15","unstructured":"MacQueen, J., et\u00a0al.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Oakland, CA, USA, vol.\u00a01, pp. 281\u2013297. (1967)"},{"issue":"1","key":"2_CR16","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/JPROC.2015.2483592","volume":"104","author":"M Nickel","year":"2015","unstructured":"Nickel, M., Murphy, K., Tresp, V., Gabrilovich, E.: A review of relational machine learning for knowledge graphs. Proc. IEEE 104(1), 11\u201333 (2015)","journal-title":"Proc. IEEE"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Rahman, T., Surma, B., Backes, M., Zhang, Y.: Fairwalk: Towards fair graph embedding (2019)","DOI":"10.24963\/ijcai.2019\/456"},{"key":"2_CR18","doi-asserted-by":"crossref","unstructured":"Shiao, W., Saini, U.S., Liu, Y., Zhao, T., Shah, N., Papalexakis, E.E.: Carl-g: clustering-accelerated representation learning on graphs. In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2036\u20132048 (2023)","DOI":"10.1145\/3580305.3599268"},{"key":"2_CR19","unstructured":"Takac, L., Zabovsky, M.: Data analysis in public social networks. In: International Scientific Conference and International Workshop Present Day Trends of Innovations, vol.\u00a01 (2012)"},{"key":"2_CR20","unstructured":"Toneva, M., Sordoni, A., Combes, R.T.d., Trischler, A., Bengio, Y., Gordon, G.J.: An empirical study of example forgetting during deep neural network learning. arXiv preprint arXiv:1812.05159 (2018)"},{"key":"2_CR21","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Wang, N., Lin, L., Li, J., Wang, H.: Unbiased graph embedding with biased graph observations. In: Proceedings of the ACM Web Conference 2022, pp. 1423\u20131433 (2022)","DOI":"10.1145\/3485447.3512189"},{"key":"2_CR23","doi-asserted-by":"crossref","unstructured":"Wu, J., He, J., Xu, J.: Net: degree-specific graph neural networks for node and graph classification. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 406\u2013415 (2019)","DOI":"10.1145\/3292500.3330950"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-8173-0_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T11:42:19Z","timestamp":1750160539000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-8173-0_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819681723","9789819681730"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-8173-0_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"18 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pakdd2025.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}