4.7 Article

Influence Analysis in Evolving Networks: A Survey

Journal

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 33, Issue 3, Pages 1045-1063

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2019.2934447

Keywords

Task analysis; Monitoring; Twitter; Mathematical model; Image edge detection; Recommender systems; Influence diffusion; influence analysis; evolving networks

Ask authors/readers for more resources

Influence analysis aims at detecting influential vertices in networks and utilizing them in cost-effective strategies. As networks evolve, incorporating network evolution into influence analysis presents new challenges. Researchers need to consider the rapid changes in networks and the incomplete understanding of network evolution by people.
Influence analysis aims at detecting influential vertices in networks and utilizing them in cost-effective business strategies. Influence analysis in large-scale networks is a key technique in many important applications ranging from viral marketing and online advertisement to recommender systems, and thus has attracted great interest from both academia and industry. Early investigations on influence analysis often assume static networks. However, it is well recognized that real networks like social networks and the web network are not static but evolve rapidly over time. Thus, to make the results of influence analysis in real networks up-to-date, we have to take network evolution into consideration. Incorporating evolution of networks into influence analysis raises many new challenges, since an evolving network often updates at a fast rate and, except for the network owner, the evolution is usually even not entirely known to people. In this survey, we provide an overview on recent research in influence analysis in evolving networks, which has not been systematically reviewed in literature. We first revisit mathematical models of evolving networks and commonly used influence models. Then, we review recent research in five major tasks of evolving network influence analysis. We also discuss some future directions to explore.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available