New trends in influence maximization models
The growing popularity of social networks is providing a promising opportunity for different
practical applications. The influence analysis is an essential technique supporting the …
practical applications. The influence analysis is an essential technique supporting the …
Influence maximization on temporal networks: a review
Influence maximization (IM) is an important topic in network science where a small seed set
is chosen to maximize the spread of influence on a network. Recently, this problem has …
is chosen to maximize the spread of influence on a network. Recently, this problem has …
Identifying influential nodes in complex networks: Effective distance gravity model
The identification of important nodes in complex networks is an area of exciting growth due
to its applications across various disciplines like disease control, data mining and network …
to its applications across various disciplines like disease control, data mining and network …
Community-based seeds selection algorithm for location aware influence maximization
In this paper, we study the location aware influence maximization problem, which finds a
seed set to maximize the influence spread on targeted users for a given query. In particular …
seed set to maximize the influence spread on targeted users for a given query. In particular …
LIDDE: A differential evolution algorithm based on local-influence-descending search strategy for influence maximization in social networks
L Qiu, X Tian, J Zhang, C Gu, S Sai - Journal of Network and Computer …, 2021 - Elsevier
Influence maximization aims to select k seed nodes from social networks so that the
expected number of nodes activated by the seed nodes can be maximized. With the …
expected number of nodes activated by the seed nodes can be maximized. With the …
[HTML][HTML] Mahe-im: multiple aggregation of heterogeneous relation embedding for influence maximization on heterogeneous information network
Y Li, L Li, Y Liu, Q Li - Expert Systems with Applications, 2022 - Elsevier
Influence maximization (IM), as an essential problem in social network analysis, can identify
a minimum group of the influential nodes to maximize the spread of information on the …
a minimum group of the influential nodes to maximize the spread of information on the …
An efficient approach to identify social disseminators for timely information diffusion
In recent years, motivated by many practical applications such as viral marketing,
researchers have paid significant attention to the circulation of information on social …
researchers have paid significant attention to the circulation of information on social …
Identification of top-k influential nodes based on discrete crow search algorithm optimization for influence maximization
Influence maximization refers to selecting a small number of influential nodes in a given
network to maximize the influence affected by the subset. In social network analysis and viral …
network to maximize the influence affected by the subset. In social network analysis and viral …
Attribute based diversification of seeds for targeted influence maximization
A Caliò, A Tagarelli - Information Sciences, 2021 - Elsevier
Embedding diversity into knowledge discovery is important: the patterns mined will be more
novel, more meaningful, and broader. Surprisingly, in the classic problem of influence …
novel, more meaningful, and broader. Surprisingly, in the classic problem of influence …
Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization
Influence maximization aims to select a subset of top-k influential nodes to maximize the
influence propagation, and it remains an open research topic of viral marketing and social …
influence propagation, and it remains an open research topic of viral marketing and social …