By now, personal life has been invaded by online social networks (OSNs) everywhere. They
intend to move more and more offline lives to online social networks. Therefore, online …

For the purpose of propagating information and ideas through a social network, a seeding
strategy aims to find a small set of seed users that are able to maximize the spread of the …

In this paper we study the adaptive complexity of submodular optimization. Informally, the
adaptive complexity of a problem is the minimal number of sequential rounds required to …

In this paper we study the adaptivity of submodular maximization. Adaptivity quantifies the
number of sequential rounds that an algorithm makes when function evaluations can be …

Given a social network G, the influence maximization (IM) problem seeks a set S of k seed
nodes in G to maximize the expected number of nodes activated via an influence cascade …

Given a social network G and an integer k, the influence maximization (IM) problem asks for
a seed set S of k nodes from G to maximize the expected number of nodes influenced via a …

The well-known influence maximization problem (IM) aims at maximizing the influence of
one information cascade in a social network by selecting appropriate seed users prior to the …

Abstract Information spreading in complex networks is often modeled as diffusing
information with certain probability from nodes that possess it to their neighbors that do not …

Influence maximization (IM) aims to identify a small number of influential individuals to
maximize the information spread and finds applications in various fields. It was first …

As a dual problem of influence maximization, the seed minimization problem asks for the
minimum number of seed nodes to influence a required number η of users in a given social …