1 citations · 1 across the 5 of their papers we have counts for
6 papers
Efficient Edge Rewiring Strategies for Enhancing PageRank Fairness
Changan Liu, Haoxin Sun, Ahad N. Zehmakan +1
We study the notion of unfairness in social networks, where a group such as females in a male-dominated industry are disadvantaged in access to important information, e.g. job post…
Promoting Fairness in Information Access within Social Networks
Changan Liu, Xiaotian Zhou, Ahad N. Zehmakan +1
The advent of online social networks has facilitated fast and wide spread of information. However, some users, especially members of minority groups, may be less likely to receive…
Efficient Algorithms for Computing Random Walk Centrality
Changan Liu, Zixuan Xie, Ahad N. Zehmakan +1
Random walk centrality is a fundamental metric in graph mining for quantifying node importance and influence, defined as the weighted average of hitting times to a node from all ot…
Fast Query of Biharmonic Distance in Networks
Changan Liu, Ahad N. Zehmakan, Zhongzhi Zhang
The \textit{biharmonic distance} (BD) is a fundamental metric that measures the distance of two nodes in a graph. It has found applications in network coherence, machine learning,…
Finding Influencers in Complex Networks: An Effective Deep Reinforcement Learning Approach
Changan Liu, Changjun Fan, Zhongzhi Zhang
Maximizing influences in complex networks is a practically important but computationally challenging task for social network analysis, due to its NP- hard nature. Most current appr…
A Fast Algorithm for Moderating Critical Nodes via Edge Removal
Changan Liu, Xiaotian Zhou, Ahad N. Zehmakan +1
Critical nodes in networks are extremely vulnerable to malicious attacks to trigger negative cascading events such as the spread of misinformation and diseases. Therefore, effectiv…