Going beyond accuracy: Estimating homophily in social networks using predictions

• Main Authors: BERRY, George, SIRIANNI, Antonio, WEBER, Ingmar, AN, Jisun, MACY, Michael
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/6045; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=7048&context=sis_research
• Institution: Singapore Management University

In online social networks, it is common to use predictions of node categories to estimate measures of homophily and other relational properties. However, online social network data often lacks basic demographic information about the nodes. Researchers must rely on predicted node attributes to estima...