Paper Info
Title
SHIM: A Novel Influence Maximization Algorithm for Targeted Marketing.
Abstract
Influence maximization is the problem of finding a set of k users in a social network, such that by targeting these k users one can maximize the spread of influence in the network. Recently a new type of social network has come into existence on platforms like Zomato and Yelp, where people can publish reviews of local businesses like restaurants, hotels, salons etc. Such social network can help owners of local businesses in making intelligent business decisions through the use of Targeted Marketing. In this paper we present Spread Heuristic based Influence Maximization SHIM algorithm, our novel algorithm, which uses a heuristic approach that maximizes the influence spread every time a node is added to the set of influential nodes. In our work, we also introduce a new method to find information-propagation probability based on attributes of the user. We test the proposed algorithm on academic dataset of Yelp, and a comprehensive performance study shows that SHIM algorithm achieves greater Influence Spread than several other algorithms.
Year
DOI
Venue
2015
10.1007/978-3-319-26832-3_31
MIKE
Field
DocType
Citations 
Publication,Heuristic,Social network,Computer science,Algorithm,Targeted marketing,Shim (computing),Maximization
Conference
0
PageRank 
References 
Authors
0.34
4
2
Name
Order
Citations
PageRank
Abhishek Gupta11410.61
Tushar Gupta211.16