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Minimum-sized influential node set selection for social networks under the independent cascade model
2014
Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '14
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problem named the Minimum-sized Influential Node Set (MINS) selection problem, which is to identify the minimum-sized set of influential nodes, such that every node in the network could be influenced ...
First, we prove that, under the independent cascade model, MINS is NP-hard. Subsequently, we present a greedy approximation algorithm to address the MINS selection problem. ...
Acknowledgment This research is partly supported by the National Science ...
doi:10.1145/2632951.2632975
dblp:conf/mobihoc/HeJBC14
fatcat:7wehnctcuza2lmykfdu3k7bngy
Spreading social influence with both positive and negative opinions in online networks
2019
Big Data Mining and Analytics
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, and propose a new optimization problem called the Minimum-sized Positive Influential Node Set (MPINS) selection problem to identify the minimum set of influential nodes such that every node in the network ...
First, we prove that, under the independent cascade model considering positive and negative influences, MPINS is APX-hard. ...
Acknowledgment This research was funded in part by the Kennesaw ...
doi:10.26599/bdma.2018.9020034
dblp:journals/bigdatama/HeHJDL19
fatcat:suxmx27w5va67kkxatxrdg4zuy
A Local Search Algorithm for the Influence Maximization Problem
2021
Frontiers in Physics
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How to select a set of top k nodes (called seeds) in a social network, through which the spread of influence under some certain diffusion models can achieve the maximum, is a major issue considered in ...
DomIM is evaluated on three real world networks, under three widely-used diffusion models, including independent cascade (IC) model, weighted cascade (WC) model, and linear threshold (LT) model. ...
selection of the most influential nodes. [34] proposed a scalable influence approximation algorithm IPA for the IMP under the IC model, which uses an independent influence path to estimate the influence ...
doi:10.3389/fphy.2021.768093
doaj:5264f0d82f9343109a71ef27fb4abc8a
fatcat:sqhczp47kjduro36w2rnmai244
Don't count the number of friends when you are spreading information in social networks
2014
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication - ICUIMC '14
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The problem of spreading information in social networks is a topic of considerable recent interest, but the conventional influence maximisation problem which selects a set of any arbitrary k nodes in a ...
network as the initially activated nodes might be inadequate in a real-world social network -cyberstalkers try to initially spread a rumour through their neighbours only rather than arbitrary users selected ...
For example, in the Independent Cascade (IC) model proposed by Goldenberg et al. ...
doi:10.1145/2557977.2557996
dblp:conf/icuimc/Kim14
fatcat:6qwowprwvve4vohr7p5ukchfta
Empirical Analysis of Seed Selection Criterion in Influence Mining for Different Classes of Networks
2013
2013 International Conference on Cloud and Green Computing
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We use two most frequently used diffusion models: Independent Cascade model and Linear Threshold model for analysis. ...
These algorithms try to select initial seed nodes effectively so as to maximize influence in a network in minimum time. ...
Kimura and Saito [17] propose two natural special cases of Independent Cascade model, which efficiently calculate good estimate of quantity for influential nodes in large scale IC based social networks ...
doi:10.1109/cgc.2013.61
dblp:conf/cgc/HussainASZ13
fatcat:44d4ktath5bxfjeostxg5lmzba
MINT
2013
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '13
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The second problem we want to study is minimum cost initial set problem, in this problem, we aim to select a set of source nodes with minimum cost such that all the other nodes can receive the information ...
The first problem is to select a set of initial source nodes, subject to budget constraint, in order to maximize the total weight of nodes that receive the information at the final stage. ...
For the Minimum Cost Initial Set (MCIS) problem, we modify the greedy algorithm to select the nodes one by one until the influential probability for each node is met. ...
doi:10.1145/2491288.2491317
dblp:conf/mobihoc/TangYLWWL13
fatcat:dmtmc33nivacvlbi2csx7mw2dm
Robust Influence Maximization
2016
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16
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We begin an investigation into this broad domain by studying robust algorithms for the Influence Maximization problem, in which the goal is to identify a set of k nodes in a social network whose joint ...
The algorithm's goal is to identify a set of k nodes who are simultaneously influential for all influence functions, compared to the (function-specific) optimum solutions. ...
Acknowledgments We would like to thank Shaddin Dughmi for useful pointers and feedback, Shishir Bharathi and Mahyar Salek for useful discussions, and anonymous reviewers for useful feedback. ...
doi:10.1145/2939672.2939760
dblp:conf/kdd/HeK16
fatcat:x747z4ui3rgh5lvx4sjr4loyiu
TSIM: A two-stage selection algorithm for influence maximization in social networks
2020
IEEE Access
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In this paper, we put forward an efficient algorithm, called a two-stage selection for influence maximization in social networks (TSIM). ...
The influence maximization problem is aimed at finding a small subset of nodes in a social./network to maximize the expected number of nodes influenced by these nodes. ...
Then, the initial active nodes in {1,4} activate their neighbor nodes under the Independent Cascade model. ...
doi:10.1109/access.2020.2966056
fatcat:ebzk6jjjdbfuze5qwfjqji7x6a
Influence Maximization Under Generic Threshold-based Non-submodular Model
[article]
2020
arXiv
pre-print
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Motivated by such social effect, the concept of influence maximization is coined, where the goal is to select a bounded number of the most influential nodes (seed nodes) from a social network so that they ...
Specifically, under this model, we first establish theories to reveal graphical conditions that ensure the network generated by node removals has the same optimal seed set as that in the original network ...
., additional edges between a pair of nodes can reduce the size of the minimum seed set for full influenceability by at most 1. ...
arXiv:2012.12309v1
fatcat:gn7b5az6xvf2vh5cmkv5cutroy
Influential Neighbours Selection for Information Diffusion in Online Social Networks
2012
2012 21st International Conference on Computer Communications and Networks (ICCCN)
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However, this model is usually unrealistic in online social networks since we cannot typically choose arbitrary nodes in the network as the initial influenced nodes. ...
A conventional problem is to select a set of any arbitrary k nodes as the initial influenced nodes so that they can effectively disseminate the information to the rest of the network. ...
ACKNOWLEDGEMENT This research is part-funded by the EU grants for the RECOGNITION project (FP7-ICT 257756) and the EPSRC DDEPI Project, EP/H003959. We thank Ben Y. Zhao for his Facebook dataset. ...
doi:10.1109/icccn.2012.6289230
dblp:conf/icccn/KimY12
fatcat:53l2wxbqdrg3vnwhdbbqespkvy
Simulation of Stance Perturbations
[article]
2023
arXiv
pre-print
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cascade of local ego networks. ...
In this work, we analyze the circumstances under which social influence operations are likely to succeed. ...
Additional support was provided by the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. ...
arXiv:2307.08511v1
fatcat:mpugkwgzhjaxtn7aena7sv4cfm
Selection of top-K influential users based on radius-neighborhood degree, multi-hops distance and selection threshold
2018
Journal of Big Data
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Then, we propose UERND D-hops algorithm for the undirected graph which is based on radius-neighborhood degree metric for selection of top-K influential users by improving the selection process of our previous ...
Influence maximization in the social network becomes increasingly important due to its various benefit and application in diverse areas. ...
; CG: coordination game; IC: independent cascade model; LT: linear threshold model. ...
doi:10.1186/s40537-018-0137-4
fatcat:pn4mb33b5ngnhf6lf2kn5dongq
Reverse Intervention for Dealing with Malicious Information in Online Social Networks
2020
Computing and informatics
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Malicious information is often hidden in the massive data flow of online social networks. ...
Therefore, this paper adopts a divide and conquer strategy and proposes an intervention algorithm based on subgraph partitioning, in which we search for some influential nodes to block or release clarification ...
Acknowlegement The authors contributed equally to this study and share the first authorship. ...
doi:10.31577/cai_2020_1-2_156
fatcat:k6cl2pbpgna4rkkfel2nlunyt4
Information cascades in complex networks
2017
Journal of Complex Networks
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NETWORKS 667 models including linear threshold model and independent cascade model are briefly reviewed in this section. ...
An information cascade can describe the spreading dynamics of rumour, disease, memes, or marketing campaigns, which initially start from a node or a set of nodes in the network. ...
Acknowledgements The authors would like to thank Ryan Ghanbari for his help with the artwork ...
doi:10.1093/comnet/cnx019
fatcat:hfu6rypv6jf65mr7sz2vmetylu
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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An exact solution is computed on smaller partitions of the network, and a candidate set of influential nodes is propagated upward to an abstract representation of the original network that maintains distance ...
Maximizing product adoption within a customer social network under a constrained advertising budget is an important special case of the general influence maximization problem. ...
Commonly used propagation models such as LTM (Linear Threshold Model) and ICM (Independent Cascade Model) assume that a node's adoption probability is conditioned on the opinions of the local network neighborhood ...
doi:10.1145/2492517.2492622
dblp:conf/asunam/MaghamiS13
fatcat:odes57tdqjgcvglrgrrd2yijuy
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