A Study on Influence Maximization in Complex Networks

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MANI SAKETH, Chennapragada VSS, PRANAY, Kakarla, SUSARLA, Akhila, RAVI RAM KARTHIK, Dukka, TANGIRALA, Jaya Lakshmi and NANDINI, YV (2023). A Study on Influence Maximization in Complex Networks. In: BHAJETA, Vikrant, CARROLL, Fiona, TAVARES, João Manuel R. S., SENGHAR, Sandeep Singh and PEER, Peter, (eds.) Intelligent Data Engineering and Analytics. Proceedings of the 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2023). Smart Innovation, Systems and Technologies (371). Singapore, Springer Nature Singapore, 111-119.

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Abstract

Influence maximization deals with finding the most influential subset from a given complex network. It is a research problem that can be resourceful for various markets, for instance, the advertising market. This study reviews the dominant algorithms in the field of influence propagation and maximization from a decade.

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Official URL:

https://link.springer.com/chapter/10.1007/978-981-...

Additional Information:

Series ISSN - 2190-3026 FICTA 2023 11-12 April, Cardiff, UK.

Page Range:

111-119

Identifiers

Identification Number:

10.1007/978-981-99-6706-3_10

ORCID:

https://orcid.org/0000-0003-0183-4093