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In the real world, a large number of social systems can be modeled as signed social networks including both positive and negative relationships. Influence maximization in signed social networks is an interesting and significant research direction, which ...

In many real-world networks, it is important to explicitly differentiate between positive and negative links, thus considering the observed networks as signed. To derive useful features, just as in the case of unsigned networks, representation learning ...

The purpose of this research is to design practical link prediction models in signed social networks. Current works focus on the sign prediction, based on the assumption that it is already known whether there is a link between any two users. In other ...

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 clustering and thus has attracted increasing attention. The majority of ...

The rapid growth of social media services brings a large amount of high-dimensional social media data at an unprecedented rate. Feature selection is powerful to prepare high-dimensional data by finding a subset of relevant features. A vast majority of ...

Recommender systems play a crucial role in mitigating the information overload problem in social media by suggesting relevant information to users. The popularity of pervasively available social activities for social media users has encouraged a large ...

We study the problem of trust inference in signed social networks, in which, in addition to rating items, users can also indicate their disposition towards each other through directional signed links. We explore the problem in a semisupervised setting, ...

Signed network analysis has attracted increasing attention in recent years. This is in part because research on signed network analysis suggests that negative links have added value in the analytical process. A major impediment in their effective use is ...

In this paper, we propose models to characterize the process of opinion spreading in signed social networks under the impact of structure balance. We classify users into different types according to their positive link numbers, and define the term user ...

Signed Networks allow explicit show of trust/distrust relationships between actors. In this poster, we provide novel measures for analyzing the following phenomena in signed networks: (i) reciprocal behavior between pairs of actors in terms of trusting/...

Influence diffusion and influence maximization in large-scale online social networks (OSNs) have been extensively studied because of their impacts on enabling effective online viral marketing. Existing studies focus on social networks with only ...

Many complex systems in the real world can be modeled as signed social networks that contain both positive and negative relations. Algorithms for mining social networks have been developed in the past, however most of them were designed primarily for ...