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New machine learning model could remove bias from social network connections


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UNIVERSITY PARK, Pa. Did you ever wonder how social networking applications like Facebook and LinkedIn make recommendations on the people you should friend or pages you should follow?
Behind the scenes are machine learning models that classify nodes based on the data they contain about users for example, their level of education, location or political affiliation. The models then use these classifications to recommend people and pages to each user. But there is significant bias in the recommendations made by these models known as graph neural networks (GNNs) as they rely on user features that are highly related to sensitive attributes such as gender or skin color. ....

Enyan Dai , Suhang Wang , International Conference On Web Search , Penn State College Of Information Sciences , National Science Foundation , Global Research Outreach , Samsung Advanced Institute Of Technology , Penn State College , Information Sciences , Web Search , Data Mining , Samsung Advanced Institute , Technology Engineering Computer Science , சர்வதேச மாநாடு ஆன் வலை தேடல் , பென் நிலை கல்லூரி ஆஃப் தகவல் அறிவியல் , தேசிய அறிவியல் அடித்தளம் , உலகளாவிய ஆராய்ச்சி ஔட்‌ரீச் , பென் நிலை கல்லூரி , தகவல் அறிவியல் , வலை தேடல் , தகவல்கள் சுரங்க , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் ,