Weighted signed networks (WSNs) are networks in which edges are labeled with positive
and negative weights. WSNs can capture like/dislike, trust/distrust, and other social …

The major task of network embedding is to learn low-dimensional vector representations of
social-network nodes. It facilitates many analytical tasks such as link prediction and node …

Graph contrastive representation learning aims to learn discriminative node representations
by contrasting positive and negative samples. It helps models learn more generalized …

The 15-year history of collaboration on Wikipedia offers insight into how peer production
communities create knowledge. In this research, we combine disparate content and …

Online social networks like Slashdot bring valuable information to millions of users-but their
accuracy is based on the integrity of their user base. Unfortunately, there are many “trolls” on …

Political conflict is an essential element of democratic systems, but can also threaten their
existence if it becomes too intense. This happens particularly when most political issues …

We consider two rival hypotheses on the emergence of organization in open production
communities. According to the first (“reputation hypothesis”), patterns of agreement and …

Since December 2010, a series of protests and uprisings have shocked North African
countries such as Tunisia, Egypt, Libya, Syria, Yemen and more. In this paper, focusing …

Adversarial social network analysis explores how social links can be altered or otherwise
manipulated to hinder unwanted information collection. To date, however, problems of this …

Community detection in signed networks is a challenging research problem, and is of great
importance to understanding the structural and functional properties of signed networks. It …