The steady growth of graph data from social networks has resulted in wide-spread research
in finding solutions to the influence maximization (IM) problem. This results in extension
of the state-of-the-art almost every year. With the recent explosion in the application of
IM in solving real-world problems, it is no longer a theoretical exercise. IM is employed
by all-and-sundry, with OnePlus series of mobile phones and Hokey Pokey ice-creams being
the most prominent industrial use-cases. Given this scenario, navigating the maze of IM
techniques to get an in-depth understanding and their utilities is of prime importance.
In this tutorial, we address this paramount issue and solve the dilemma of “Which IM
technique to use and under What scenarios”? “What does it really mean to claim to be the
state-of-the-art”?
This tutorial builds upon our benchmarking study and will provide a concise and intuitive
overview of the most important IM techniques, which is usually lost in the technical
literature. More fundamentally, we will unearth a series of incorrect claims made by
prominent IM papers, disseminate the inherent deficiencies of existing approaches and
surface the open challenges in IM even after a decade of research.
Dr. Akhil Arora
Dr. Sainyam Galhotra
Dr. Sayan Ranu
Dr. Shourya Roy
