Abstract
The steady growth of graph data from social networks has resulted in wide-spread research on the influence maximization (IM) problem. This results in extension of the state-of-the-art almost every year. This tutorial 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. It will also include a hands-on component where the participants will have the opportunity to evaluate our findings on their computers using an easy-to-use Python API.

Presenters
Akhil Arora,Sainyam Galhotra and Sayan Ranu