Signed Node Relevance Measurements
Tyler Derr (1), Chenxing Wang (1), Suhang Wang (2), Jiliang Tang (1), ((1) Michigan State University, (2) Arizona State University)

TL;DR
This paper introduces and evaluates various relevance measurements for nodes in signed social networks, linking them to balance theory and network properties, with experiments on real datasets.
Contribution
It presents new relevance measurements for signed networks from local and global views, connecting them to balance theory and network characteristics.
Findings
Relevance measurements impact signed network analysis tasks.
Experimental results validate the effectiveness of proposed measurements.
Connections between relevance measures and network properties are established.
Abstract
In this paper, we perform the initial and comprehensive study on the problem of measuring node relevance on signed social networks. We design numerous relevance measurements for signed social networks from both local and global perspectives and investigate the connection between signed relevance measurements, balance theory and signed network properties. Experimental results are conducted to study the effects of signed relevance measurements with four real-world datasets on signed network analysis tasks.
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Taxonomy
TopicsComplex Network Analysis Techniques · Advanced Graph Neural Networks · Peer-to-Peer Network Technologies
