TY - GEN
T1 - On the information unfairness of social networks
AU - Jalali, Zeinab S.
AU - Wang, Weixiang
AU - Kim, Myunghwan
AU - Raghavan, Hema
AU - Soundarajan, Sucheta
N1 - Publisher Copyright:
© 2020 by SIAM.
PY - 2020
Y1 - 2020
N2 - Social networks play a vital role in the spread of information through a population, and individuals in networks make important life decisions on the basis of the information to which they have access. In many cases, it is important to evaluate whether information is spreading fairly to all groups in a network. For instance, are male and female students equally likely to hear about a new scholarship? In this paper, we present the information unfairness criterion, which measures whether information spreads fairly to all groups in a network. We perform a thorough case study on the DBLP computer science co-authorship network with respect to gender. We then propose MaxFair, an algorithm to add edges to a network to decrease information unfairness, and evaluate on several real-world network datasets.
AB - Social networks play a vital role in the spread of information through a population, and individuals in networks make important life decisions on the basis of the information to which they have access. In many cases, it is important to evaluate whether information is spreading fairly to all groups in a network. For instance, are male and female students equally likely to hear about a new scholarship? In this paper, we present the information unfairness criterion, which measures whether information spreads fairly to all groups in a network. We perform a thorough case study on the DBLP computer science co-authorship network with respect to gender. We then propose MaxFair, an algorithm to add edges to a network to decrease information unfairness, and evaluate on several real-world network datasets.
UR - http://www.scopus.com/inward/record.url?scp=85089201300&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85089201300&partnerID=8YFLogxK
U2 - 10.1137/1.9781611976236.69
DO - 10.1137/1.9781611976236.69
M3 - Conference contribution
AN - SCOPUS:85089201300
T3 - Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020
SP - 613
EP - 621
BT - Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020
A2 - Demeniconi, Carlotta
A2 - Chawla, Nitesh
PB - Society for Industrial and Applied Mathematics Publications
T2 - 2020 SIAM International Conference on Data Mining, SDM 2020
Y2 - 7 May 2020 through 9 May 2020
ER -