Affiliation:
1. University of Auckland and Pingar, Pingar
2. University of Auckland, Pingar
3. Pingar,Pingar
Abstract
Top-
k
nodes are the important actors for a subjectively determined topic in a social network. To some extent, a topic is taken as a ranking criteria for identifying top-
k
nodes. Within a viral marketing network, subjectively selected topics can include the following: Who can promote a new product to the largest number of people, and who are the highest spending customers? Based on these questions, there has been a growing interest in top-
k
nodes research to effectively identify key players. In this article, we review and classify existing literature on top-
k
nodes identification into two major categories: top-
k
influential nodes and top-
k
significant nodes. We survey both theoretical and applied work in the field and describe promising research directions based on our review. This research area has proven to be beneficial for data analysis on online social networks as well as practical applications on real-life networks.
Funder
Callaghan Innovation, under an R8D Student Fellowship
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
37 articles.
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