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DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades
[chapter]
2018
Studies in Computational Intelligence
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Traditional solutions focus on the algorithmic aspect of the problem and are based solely on static networks. ...
We compare it with four different prevalent influence maximization approaches, on a large scale Chinese microblogging dataset. ...
In addition, we utilize an evaluation methodology based on actual diffusion cascades, as a more realistic alternative to epidemic simulation models. ...
doi:10.1007/978-3-030-05411-3_32
fatcat:d2srt7g4g5fwhjckqrme7p4nia
Maximizing the spread of influence through a social network
2003
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '03
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based on the well-studied notions of degree centrality and distance centrality from the field of social networks. ...
Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the ...
The influence maximization problem is NP-hard for the Independent Cascade model.
Proof. ...
doi:10.1145/956750.956769
dblp:conf/kdd/KempeKT03
fatcat:m45iziilfrgczdgc3a2mvlduka
Maximizing the spread of influence through a social network
2003
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '03
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based on the well-studied notions of degree centrality and distance centrality from the field of social networks. ...
Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the ...
The influence maximization problem is NP-hard for the Independent Cascade model.
Proof. ...
doi:10.1145/956755.956769
fatcat:2ugfloaiebhodflm4zsrhzg6ja
Multi-task Learning for Influence Estimation and Maximization
[article]
2020
arXiv
pre-print
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), a unified approach that uses representations learned from diffusion cascades to perform model-independent influence maximization that scales in real-world datasets. ...
Motivated by the recent criticism on the effectiveness of diffusion models as well as the galloping advancements in influence learning, we propose IMINFECTOR (Influence Maximization with INFluencer vECTORs ...
A stochastic diffusion model, such as the independent cascade [1] , governs how an epidemic traverses the users based on their connections. ...
arXiv:1904.08804v3
fatcat:he3qzlitrzgnhofp36432emjqi
Link recommendation for promoting information diffusion in social networks
2013
Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion
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Experimental results on Email dataset and Amazon dataset under Independent Cascade Model and Linear Threshold Model show that our method noticeably outperforms the traditional methods in terms of promoting ...
Most of current link recommendation researches only focus on strengthening the social interaction function, but ignore the problem of how to enhance the information diffusion function. ...
This work is supported by the Natural Science Foundation of China (No. 61173074) and the ZTE cooperation project (No. MH20120428). ...
doi:10.1145/2487788.2487881
dblp:conf/www/LiXLSGS13
fatcat:hjh2jswej5e3jc57f22ga67pqq
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently
[article]
2020
arXiv
pre-print
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2019 pre-print arXiv:1909.05416v1 fatcat:53ts3nse5zgrzoqa646pbitqpi
Related optimization, including influence maximization, model parameter inference, or the development of vaccination strategies, relies heavily on sampling from a model. ...
As alternative, we present an efficient message passing algorithm that computes the probability distribution of the cascade size for the Independent Cascade Model on weighted directed networks and generalizations ...
Acknowledgments RB and JQ were supported by a grant from the US National Cancer Institute (1R35CA220523). ...
arXiv:1909.05416v2
fatcat:tfakl7l45vgcfbbgcapf7zm52e
Realistic influence maximization based on followers score and engagement grade on instagram
2021
Bulletin of Electrical Engineering and Informatics
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In this study, two diffusion models are proposed, which are based on the original IC and LT models, with the addition of the engagement grade (EG) factor. ...
In recent years, the emergence of social media influencers attracts the study of a realistic influence maximization (IM) technique. The theoretical performance of IM has become matured. ...
IM diffusion models This study proposes two diffusion models, namely IC-eg (independent cascade-EG) and LT-eg (linear threshold-EG). ...
doi:10.11591/eei.v10i2.2656
fatcat:jlhn6ye22zddjadlit4g2vxfl4
Incentive Compatible Influence Maximization in Social Networks and Application to Viral Marketing
[article]
2011
arXiv
pre-print
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In the second model, the influencer-influencee model, which is more realistic, we determine influence probabilities by combining the probability values reported by the influencers and influencees. ...
Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. ...
In the second model, the influencer-influencee model , which is more realistic, we determine influence probabilities by combining the probability values reported by the influencers and influencees. ...
arXiv:1102.0918v2
fatcat:k63nph5mlrdlvcxelbobznozry
A Review of Critical Research Areas under Information Diffusion in Social Networks
2020
International Journal of Advanced Computer Science and Applications
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The review also identifies the methodologies, features and aspects studied in the current literature and proposes the optimal feature set to improve performance. ...
This review will enable researchers to quickly identify the research areas, the current gaps and steer them into the possible future directions associated with them. ...
Influence models based on time are also generally an extension of Independent cascade model or Linear Threshold Model. ...
doi:10.14569/ijacsa.2020.0110454
fatcat:pvbpbhzghzfsxgsy4q5bii3blq
Exploiting Historical Diffusion Data to Maximize Information Spread in Social Networks
2015
International Journal of Database Theory and Application
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Based on Local Influence Model, we use greedy algorithm to find an approximate optimal solution. ...
Moreover, motivated by the social influence locality, we propose a Local Influence Model to evaluate node's influence within a local area instead of the whole network, which can effectively reduce the ...
Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No.61271252 and No.61202482), the Specialized Research Fund for the Doctoral Program of Higher Education ...
doi:10.14257/ijdta.2015.8.2.18
fatcat:2nkpd2jpzfgl5dw7jibgcrest4
Relative influence maximization in competitive social networks
2017
Science China Information Sciences
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To describe the spread of two competitive opinions, we introduce a competitive independent cas-cade (CIC) model by extending the classical independent cascade (IC) model [3] . ...
In CIC model, each individual is in one of three states, i.e., inactive, P-active and N-active. Individuals in inactive states are not influenced. ...
To describe the spread of two competitive opinions, we introduce a competitive independent cas-cade (CIC) model by extending the classical independent cascade (IC) model [3] . ...
doi:10.1007/s11432-016-9080-3
fatcat:otb5ire555cf5nwjgcxvpdoova
Hierarchical influence maximization for advertising in multi-agent markets
2013
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13
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products to the same consumer base. ...
Our proposed method scales to much larger networks and outperforms other influence maximization techniques on marketing products. ...
network, based on a known influence propagation model. ...
doi:10.1145/2492517.2492622
dblp:conf/asunam/MaghamiS13
fatcat:odes57tdqjgcvglrgrrd2yijuy
GetReal
2015
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data - SIGMOD '15
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State-of-the-art classical influence maximization (im) techniques are "competition-unaware" as they assume that a group (company) finds seeds (users) in a network independent of other groups who are also ...
In this paper, we propose a novel framework based on game theory to provide a more realistic solution to the im problem in competitive networks by jettisoning these unrealistic assumptions. ...
To facilitate our discussion, we focus on the Independent Cascade (ic) and Weighted Cascade (wc) models as these are the most popular cascade models [7, 8, [18] [19] [20] . ...
doi:10.1145/2723372.2723710
dblp:conf/sigmod/LiBCGM15
fatcat:n34p5kvqizev3h4kjfrpkvcogu
Influence Maximization with Spontaneous User Adoption
2020
Proceedings of the 13th International Conference on Web Search and Data Mining
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We incorporate the realistic scenario of spontaneous user adoption into influence propagation (also refer to as self-activation) and propose the self-activation independent cascade (SAIC) model: nodes ...
Under the SAIC model, we study three influence maximization problems: (a) boosted influence maximization (BIM) aims to maximize the total influence spread from both self-activated nodes and selected seeds ...
We first incorporate self activation with the classical independent cascade (IC) model to propose the self-activation independent cascade (SAIC) model of influence propagation. ...
doi:10.1145/3336191.3371791
dblp:conf/wsdm/SunCYC20
fatcat:pme3eq3amndl3epyl52pm3fqya
Maximizing the Spread of Influence through a Social Network
2015
Theory of Computing
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The framework proposed in [68], on the other hand, is based on a simple linear model where the solution to the optimization problem can be obtained by solving a system of linear equations. ...
based on the well-studied notions of degree centrality and distance centrality from the field of social networks. ...
Acknowledgments We would like to thank anonymous reviewers of the conference and journal versions of this paper for useful feedback. ...
doi:10.4086/toc.2015.v011a004
dblp:journals/toc/KempeKT15
fatcat:3mdtb55b5za63cjouvif6m7l2i
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