Results 11 to 20 of about 6,507,474 (284)
Robust Influence Maximization [PDF]
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016 12 pages, 4 figures, Technical Report, contains proofs for the paper appeared in KDD ...
Wei Chen 0013 +4 more
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Influence Maximization Using Influence and Susceptibility Embeddings [PDF]
Proceedings of the International AAAI Conference on Web and Social Media, 2020 Finding a set of users that can maximize the spread of information in a social network is an important problem in social media analysis — being a critical part of several real-world applications such as viral marketing, political advertising and epidemiology.
Panagopoulos, George +2 more
core +8 more sources
Influence Maximization in Hypergraphs [PDF]
CoRR, 2022 Influence maximization in complex networks, i.e., maximizing the size of influenced nodes via selecting K seed nodes for a given spreading process, has attracted great attention in recent years. However, the influence maximization problem in hypergraphs, in which the hyperedges are leveraged to represent the interactions among more than two nodes, is ...
Ming Xie +3 more
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Online Influence Maximization [PDF]
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015 Social networks are commonly used for marketing purposes. For example, free samples of a product can be given to a few influential social network users (or seed nodes), with the hope that they will convince their friends to buy it. One way to formalize this objective is through the problem of influence maximization (or IM), whose goal is to find the ...
Lei, Siyu +4 more
core +9 more sources
Online influence maximization [PDF]
, 2016 Social networks, such as Twitter and Facebook, enable the wide spread of information through users’ influence on each other. These networks are very useful for marketing purposes. For example, free samples of a product can be given to a few influencers (seed nodes), with the hope that they will convince their friends to buy it.
Lei, Siyu, 雷思宇
openaire +4 more sources
Community-diversified influence maximization in social networks [PDF]
, 2020 To meet the requirement of social influence analytics in various applications, the problem of influence maximization has been studied in recent years. The aim is to find a limited number of nodes (i.e., users) which can activate (i.e.
Li, Jianxin +6 more
core +2 more sources
Influence Learning and Maximization [PDF]
, 2021 The problem of maximizing or minimizing the spreading in a social network has become more timely than ever with the advent of fake news and the coronavirus epidemic. The solution to this problem pertains to influence maximization algorithms that identify the right nodes to lockdown for epidemic containment, hire for viral marketing campaigns, block for
Panagopoulos, George +1 more
openaire +3 more sources
Stability of influence maximization [PDF]
Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 2014 Erratum of Paper "Stability of Influence Maximization" which was presented and published in the ...
Xinran He, David Kempe 0001
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Target-Aware Holistic Influence Maximization in Spatial Social Networks
, 2022 Influence maximization has recently received significant attention for scheduling online campaigns or advertisements on social network platforms. However, most studies only focus on user influence via cyber interactions while ignoring their physical ...
Li, Jianxin +5 more
core +2 more sources
Adversarial Influence Maximization [PDF]
2019 IEEE International Symposium on Information Theory (ISIT), 2019 We consider the problem of influence maximization in fixed networks for contagion models in an adversarial setting. The goal is to select an optimal set of nodes to seed the influence process, such that the number of influenced nodes at the conclusion of the campaign is as large as possible.
Justin Khim, Varun S. Jog, Po-Ling Loh
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