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Influence Maximization With Visual Analytics
IEEE Transactions on Visualization and Computer Graphics, 2022 In social networks, individuals' decisions are strongly influenced by recommendations from their friends, acquaintances, and favorite renowned personalities. The popularity of online social networking platforms makes them the prime venues to advertise products and promote opinions. The Influence Maximization (IM) problem entails selecting a seed set of
Alessio Arleo +4 more
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Influence Maximization Based on Backward Reasoning in Online Social Networks
Mathematics, 2021 Along with the rapid development of information technology, online social networks have become more and more popular, which has greatly changed the way of information diffusion.
Lin Zhang, Kan Li
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Influence maximization diffusion models based on engagement and activeness on instagram
Journal of King Saud University: Computer and Information Sciences, 2022 An influencer is an impactful content creator on social media. The emergence of influencers led to increased influencer marketing. The task of picking the right influencers is widely studied through influence maximization (IM).
Kristo Radion Purba +2 more
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IEEE Access, 2020 Influence maximization is to select k nodes from social networks to maximize the expected number of nodes activated by these selected nodes. Influence maximization problem plays a vital role in commercial marketing, news propagation, rumor control and ...
Liqing Qiu +3 more
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CM2D: Cost Minimization Under the Competitive Market in Dynamic Social Networks
IEEE Access, 2020 The Reverse Influence Maximization (RIM) model deals with the viral marketing cost minimization in social networks. On the other hand, the Influence maximization (IM) technique finds the small number of influential users that maximize the viral marketing
Ashis Talukder, Choong Seon Hong
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Time-Constrained Adaptive Influence Maximization [PDF]
IEEE Transactions on Computational Social Systems, 2021 The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffusion process. In its adaptive version, additional seed users can be selected after observing certain diffusion results.
Guangmo Tong +3 more
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A Novel Nested Q-Learning Method to Tackle Time-Constrained Competitive Influence Maximization
IEEE Access, 2019 Time plays a critical role in competitive influence maximization. Companies aim to promote their products before certain events, such as Christmas Eve or music concerts, to gain more benefit under competitions from other companies.
Khurshed Ali, Chih-Yu Wang, Yi-Shin Chen
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Context-based influence maximization with privacy protection in social networks
EURASIP Journal on Wireless Communications and Networking, 2019 As the increase of requirements of accessing and sharing information of people, large social networks have appeared. The influence maximization over social network has been a popular research topic, whose goal is to maximize the expected range of ...
Dong Jing, Ting Liu
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Knapsack-Based Reverse Influence Maximization for Target Marketing in Social Networks
IEEE Access, 2019 With the dramatic proliferation in recent years, the social networks have become a ubiquitous medium of marketing and the influence maximization (IM) technique, being such a viral marketing tool, has gained significant research interest in recent years ...
Ashis Talukder +4 more
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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.
Khim, Justin, Jog, Varun, Loh, Po-Ling
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