Influence maximization for viral marketing in online social networks (part a)

• Main Author: Ooi, Mei Wah
• Other Authors: Tang Xueyan
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Library and information science
• Online Access: http://hdl.handle.net/10356/74049
• Institution: Nanyang Technological University

In the recent years, there has been a drastic rise of users on social media platforms such as Facebook, Twitter and Instagram. As such, marketers and advertisers have turned to social media platforms for great media exposure. Viral marketing is a strategy in which new products or activities are advertised by some influential users. However, to search for the best candidate to spread the influence as widely as possible is an issue. Influence maximization is a technique whereby a seed set is selected based on online social network graphs and diffusion model of influence propagation. By using the influence maximization, based on the resultant seed set, the most influential candidate can therefore be found. The purpose of the project is to develop a software tool for influence maximization. The main functionality of the software tool is to compute the seed set for influence maximization based on a given OSN graph and a diffusion model of influence propagation.