{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fairwalk-towards-fair-graph-embedding","title":"Fairwalk: Towards fair graph embedding","arxiv_id":null,"date":"2019-01-01","proceeding":"IJCAI 2019 1","authors":["Tahleen Rahman","Bartlomiej Surma","Michael Backes and Yang Zhang"],"abstract":"Graph embeddings have gained huge popularity in\r\nthe recent years as a powerful tool to analyze social networks. However, no prior works have studied potential bias issues inherent within graph embedding. In this paper, we make a first attempt in\r\nthis direction. In particular, we concentrate on the\r\nfairness of node2vec, a popular graph embedding\r\nmethod. Our analyses on two real-world datasets\r\ndemonstrate the existence of bias in node2vec when\r\nused for friendship recommendation. We therefore propose a fairness-aware embedding method,\r\nnamely Fairwalk, which extends node2vec. Experimental results demonstrate that Fairwalk reduces\r\nbias under multiple fairness metrics while still preserving the utility","url_abs":"https://yangzhangalmo.github.io/papers/IJCAI19.pdf","url_pdf":"https://yangzhangalmo.github.io/papers/IJCAI19.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fairwalk-towards-fair-graph-embedding","repo_url":"https://github.com/EnderGed/Fairwalk","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"fairwalk-towards-fair-graph-embedding","repo_url":"https://github.com/urielsinger/fairwalk","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"fairness","task_name":"Fairness"},{"task_slug":"graph-embedding","task_name":"Graph Embedding"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}