Signed-PageRank: An Efficient Influence Maximization Framework for Signed Social Networks

@article{Yin2021SignedPageRankAE,
  title={Signed-PageRank: An Efficient Influence Maximization Framework for Signed Social Networks},
  author={Xiaoyan Yin and Xiao Hu and Yanjiao Chen and Xu Yuan and Baochun Li},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2021},
  volume={33},
  pages={2208-2222}
}
Influence maximization in social networks is of great importance for marketing new products. Signed social networks with both positive (friends) and negative (foes) relationships pose new challenges and opportunities, since the influence of negative relationships can be leveraged to promote information propagation. In this paper, we study the problem of influence maximization for advertisement recommendation in signed social networks. We propose a new framework to characterize the information… 
View on IEEE
iqua.ece.toronto.edu
11 Citations
Background Citations
5
Methods Citations
1

11 Citations

Citation Type

Citation Type

Net positive influence maximization in signed social networks
TLDR
The concept of net positive influence is introduced and an improved R-Greedy algorithm is proposed to solve the NPIM problem for signed social networks, to select the seed set with as much positive influence as possible and as less negative influence as Possible.
Time-sensitive Positive Influence Maximization in signed social networks
Parallel social behavior-based algorithm for identification of influential users in social network
TLDR
This paper introduces a new parallel algorithm, named PSAIIM, for identification of influential users in social network, which uses the community structure to apply perfect parallelism to the CPU architecture of the machines to compute an optimal set of influential nodes.
POLE: Polarized Embedding for Signed Networks
TLDR
POLE (POLarized Embedding for signed networks), a signed embedding method for polarized graphs that captures both topological and signed similarities jointly via signed autocovariance, significantly outperforms state-of-the-art methods in signed link prediction, particularly for negative links with gains of up to one order of magnitude.
A Novel Greedy FluidSpread Algorithm With Equilibrium Temperature for Influence Diffusion in Social Networks
TLDR
In this article, the behavior of the users, such as the interactions and relationships of each user, and the content of a topic are modeled to the user interest vector and the topic distribution vector, respectively, to calculate the information acceptance probability.
ComPath: User Interest Mining in Heterogeneous Signed Social Networks for Internet of People
TLDR
A new proximity function that measures the similarity between users based on their interests/disinterests with respect to the relative popularity of these interests/ Disinterests among other users and a greedy community detection algorithm that detects communities of users with common interests with possible overlapping communities using the adaptive clique relaxation technique are proposed.
Spam Classification Based on Signed Network Analysis
TLDR
A signed-network-analysis-based spam classification method that assumes that the edge signs are highly likely to be determined by considering users’ social relationships, so there will be a substantial difference between the edge sign patterns of spammers and that of non-spammers.
Betweenness Approximation for Hypernetwork Dismantling with Hypergraph Neural Network
TLDR
This paper proposes a novel HyperNetwork Dismantling methods based on hypergraph neural network, called HND, which outperforms various baselines and is utilized to approximate the nodes’ betweenness in real world hypernetworks and further used for dismantling.
A Blockchain-Based Microgrid Data Disaster Backup Scheme in Edge Computing
TLDR
A microgrid data disaster backup scheme based on blockchain in edge computing environment and the traditional proof of authority (PoA) consensus mechanism is improved partially, and the improved PoA is used to make each node reach consensus and pack blocks on the chain.
Network Centrality Measures: Role and Importance in Social Networks
...
...

References

SHOWING 1-10 OF 43 REFERENCES
Influence Maximization on Signed Social Networks with Integrated PageRank
  • Shubo Chen, Kejing He
  • Computer Science
    2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)
  • 2015
TLDR
This paper integrates the PageRank on signed social networks and uses the integrated PageRank to study influence maximization in OSNs with both friend and hostile relations which are respected as positive edges and negative edges on signed networks.
Polarity Related Influence Maximization in Signed Social Networks
TLDR
The polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks is proposed and a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem insigned social networks.
Influence Maximization on Social Graphs: A Survey
TLDR
This paper surveys and synthesizes a wide spectrum of existing studies on IM from an algorithmic perspective, with a special focus on a review of well-accepted diffusion models that capture the information diffusion process and build the foundation of the IM problem.
Positive influence maximization in signed social networks based on simulated annealing
Applications of Structural Balance in Signed Social Networks
TLDR
This article introduces several new signed network analysis methods that exploit structural balance for measuring partial balance, for finding communities of people based on Balance, for drawing signed social networks, and for solving the problem of link prediction.
Recommendations in Signed Social Networks
TLDR
This work provides a principled and mathematical approach to exploit signed social networks for recommendation, and proposes a model, RecSSN, to leverage positive and negative links insigned social networks.
Voter Model on Signed Social Networks
TLDR
This study makes the first attempt to investigate the influence diffusion and influence maximization in OSNs with both friend and foe relations, which are modeled using positive and negative edges on signed networks and develops efficient algorithms to select initial seeds of one opinion that maximize either its short-term influence coverage or long-term steady state influence coverage.
Influence maximization on signed networks under independent cascade model
TLDR
This work addresses an independent cascade diffusion model in the signed network for describing two opposite types of influence spreading in a signed network, and presents an efficient influence maximization method in signed networks.
Influence diffusion dynamics and influence maximization in social networks with friend and foe relationships
TLDR
This paper extends the classic voter model to signed networks and analyzes the dynamics of influence diffusion of two opposite opinions, which are modeled using positive and negative edges on signed networks to solve the influence maximization problem.
Personalized Ranking in Signed Networks Using Signed Random Walk with Restart
TLDR
Signed Random Walk with Restart is proposed, a novel model for personalized ranking in signed networks that provides proper rankings reflecting signed edges based on the signed surfer and achieves the best accuracy for sign prediction and predicts trolls 4× more accurately than other ranking models.
...
...