Social network user influence sense-making and dynamics prediction
Identifying influential users and predicting their “network impact” on social networks have
attracted tremendous interest from both academia and industry. Various definitions of …
attracted tremendous interest from both academia and industry. Various definitions of …
Social network user influence dynamics prediction
Identifying influential users and predicting their “network impact” on social networks have
attracted tremendous interest from both academia and industry. Most of the developed …
attracted tremendous interest from both academia and industry. Most of the developed …
Learning influence probabilities and modelling influence diffusion in twitter
Influence diffusion has been widely studied in social networks for applications such as
service promotion and marketing. There are two challenging issues here:(1) how we …
service promotion and marketing. There are two challenging issues here:(1) how we …
Models of influence in online social networks
Online social networks gained their popularity from relationships users can build with each
other. These social ties play an important role in asserting users' behaviors in a social …
other. These social ties play an important role in asserting users' behaviors in a social …
Modeling influence with semantics in social networks: A survey
G Razis, I Anagnostopoulos, S Zeadally - ACM Computing Surveys …, 2020 - dl.acm.org
The discovery of influential entities in all kinds of networks (eg, social, digital, or computer)
has always been an important field of study. In recent years, Online Social Networks (OSNs) …
has always been an important field of study. In recent years, Online Social Networks (OSNs) …
Csi: Community-level social influence analysis
Y Mehmood, N Barbieri, F Bonchi… - Machine Learning and …, 2013 - Springer
Modeling how information propagates in social networks driven by peer influence, is a
fundamental research question towards understanding the structure and dynamics of these …
fundamental research question towards understanding the structure and dynamics of these …
Identification of influencers in online social networks: measuring influence considering multidimensional factors exploration
YB Zhuang, ZH Li, YJ Zhuang - Heliyon, 2021 - cell.com
Online Social networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify influencers is thus very significant, allowing us to control …
structure and function. To identify influencers is thus very significant, allowing us to control …
An efficient two-phase model for computing influential nodes in social networks using social actions
M Azaouzi, LB Romdhane - Journal of Computer Science and Technology, 2018 - Springer
The measurement of influence in social networks has received a lot of attention in the data
mining community. Influence maximization refers to the process of finding influential users …
mining community. Influence maximization refers to the process of finding influential users …
Influence maximization in social networks: A survey of behaviour-aware methods
A Zareie, R Sakellariou - Social Network Analysis and Mining, 2023 - Springer
Social networks have become an increasingly common abstraction to capture the
interactions of individual users in a number of everyday activities and applications. As a …
interactions of individual users in a number of everyday activities and applications. As a …
A parameterizable influence spread-based centrality measure for influential users detection in social networks
F Riquelme, JA Vera - Knowledge-Based Systems, 2022 - Elsevier
In social network analysis, centrality refers to the relevance of actors or nodes within a social
network represented as a graph. Traditional centrality measures are based on topological …
network represented as a graph. Traditional centrality measures are based on topological …