With the rapid growth of the online social networks like Facebook and Twitter, Viral Marketing,
also known as “word-of-mouth marketing”, is an effective strategy for advertising various products
in the social network. Influence maximization is to find a small subset of individuals that can bring
the maximum cascading effects of the influence spread.
In this thesis, we study an efficient algorithm for influence maximization. Finally, our experimental
results show that our algorithms outperform existing methods.
Permanent URL for this record: https://lbezone.hkust.edu.hk/bib/b1514760