Abstract
Viral marketing works with a social network as its backbone, where social interactions help spreading a message from one person to another. In social networks, a node with a higher degree can reach larger number of nodes in a single hop, and hence can be considered to be more influential than a node with lesser degree. For viral marketing with limited resources, initially the seller can focus on marketing the product to a certain influential group of individuals, here mentioned as core. If k persons are targeted for initial marketing, then the objective is to find the initial set of k active nodes, which will facilitate the spread most efficiently. We did a degree based scaling in graphs for making the edge weights suitable for degree based spreading. Then we detect the core from the maximum spanning tree (MST) of the graph by finding the top k influential nodes and the paths in MST that joins them. The paths within the core depict the key interaction sequences that will trigger the spread within the network. Experimental results show that the set of k influential nodes found by our core finding method spreads information faster than the greedy k-center method for the same k value.
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Chaudhury, A., Basuchowdhuri, P., Majumder, S. (2012). Spread of Information in a Social Network Using Influential Nodes. In: Tan, PN., Chawla, S., Ho, C.K., Bailey, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2012. Lecture Notes in Computer Science(), vol 7302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30220-6_11
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DOI: https://doi.org/10.1007/978-3-642-30220-6_11
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