Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …

Given a social network G and a positive integer k, the influence maximization problem asks
for k nodes (in G) whose adoptions of a certain idea or product can trigger the largest …

To meet the requirement of social influence analytics in various applications, the problem of
influence maximization has been studied in recent years. The aim is to find a limited number …

Influence maximization has recently received significant attention for scheduling online
campaigns or advertisements on social network platforms. However, most studies only focus …

Research on social networks has exploded over the last decade. To a large extent, this has
been fueled by the spectacular growth of social media and online social networking sites …

Influence maximization (IM) is the process of choosing a set of seeds from a social network
so that the most individuals will be influenced by them. Calculating the social effect of a …

Online social networks play a major role not only in socio psychological front, but also in the
economic aspect. The way social network serves as a platform of information spread, has …

If a piece of information is released from a set of media sites, can it spread, in 1 month, to a
million web pages? Can we efficiently find a small set of media sites among millions that can …

Software-defined vehicular network (SDVN) is a promising networking paradigm that can
provide intelligent information exchanges by separating network management and data …

Given a social network G with n nodes and m edges, a positive integer k, and a cascade
model C, the influence maximization (IM) problem asks for k nodes in G such that the …