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Seed selection for viral marketing in online social networks : from influence maximization to profit maximization
| Content Provider | Semantic Scholar |
|---|---|
| Author | Tang, Jing |
| Copyright Year | 2017 |
| Abstract | Online Social Networks (OSNs) attract billions of users. Information can be disseminated widely and rapidly through OSNs with “word-of-mouth” effects. Viral marketing is such a typical application in which new products or commercial activities are advertised by some seed users in OSNs to other users in a cascading manner. A large amount of recent work has been focusing on viral marketing in OSNs. In this thesis, three seed selection problems in viral marketing are investigated. We start from the classical influence maximization. Then, we look at profit maximization for advertisers and OSN providers respectively that naturally combines the benefit with the cost of viral marketing. Recent research has adopted the sampling approach to achieve a (1 − 1/e − ε)approximation guarantee for influence maximization. One fundamental step of this approach is to examine the approximation assurance of the seed set constructed under a given number of samples generated. We focus on this essential step and propose a framework to Maximize the online Approximation Guarantee (MAG). Our framework exploits instance-specific information during execution to construct online bounds that can potentially break the conventional approximation limit of (1 − 1/e). The applications of MAG are two-fold. First, MAG can provide online approximation guarantees for runtime-restricted influence maximization in which only a limited amount of execution time is allowed to generate samples for influence estimation. Second, by deriving a better online approximation guarantee, MAG can be used to save the running time needed to reach an approximation target for traditional influence maximization. The selection of initial seed users yields a tradeoff between the expense and reward of viral marketing. We define a profit metric that combines the benefit of influence spread with the cost of seed selection in viral marketing. We carry out a comprehensive study on finding a set of seed nodes to maximize the profit of viral marketing. We show that |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://repository.ntu.edu.sg/bitstream/handle/10356/72857/%5BTANG%20Jing%5D%20Thesis%202017.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
