Dynamics of information diffusion and its applications on complex networks

ZK Zhang, C Liu, XX Zhan, X Lu, CX Zhang, YC Zhang - Physics Reports, 2016 - Elsevier
The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the
information of effective transmission from heterogeneous individuals to various systems …

Multi-topic misinformation blocking with budget constraint on online social networks

DV Pham, GL Nguyen, TN Nguyen, CV Pham… - IEEE …, 2020 - ieeexplore.ieee.org
Along with the development of Information Technology, Online Social Networks (OSN) are
constantly developing and have become popular media in the world. Besides …

[HTML][HTML] Influence maximization on temporal networks: a review

E Yanchenko, T Murata, P Holme - Applied Network Science, 2024 - Springer
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 …

Graph vulnerability and robustness: A survey

S Freitas, D Yang, S Kumar, H Tong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The study of network robustness is a critical tool in the characterization and sense making of
complex interconnected systems such as infrastructure, communication and social networks …

Analysis, prediction, and control of epidemics: A survey from scalar to dynamic network models

L Zino, M Cao - IEEE Circuits and Systems Magazine, 2021 - ieeexplore.ieee.org
During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading have
emerged as powerful tools to produce valuable predictions of the evolution of the pandemic …

Gotcha! network-based fraud detection for social security fraud

V Van Vlasselaer, T Eliassi-Rad… - Management …, 2017 - pubsonline.informs.org
We study the impact of network information for social security fraud detection. In a social
security system, companies have to pay taxes to the government. This study aims to identify …

Gelling, and melting, large graphs by edge manipulation

H Tong, BA Prakash, T Eliassi-Rad… - Proceedings of the 21st …, 2012 - dl.acm.org
Controlling the dissemination of an entity (eg, meme, virus, etc) on a large graph is an
interesting problem in many disciplines. Examples include epidemiology, computer security …

Spotting culprits in epidemics: How many and which ones?

BA Prakash, J Vreeken… - 2012 IEEE 12th …, 2012 - ieeexplore.ieee.org
Given a snapshot of a large graph, in which an infection has been spreading for some time,
can we identify those nodes from which the infection started to spread? In other words, can …

Threshold conditions for arbitrary cascade models on arbitrary networks

BA Prakash, D Chakrabarti, NC Valler… - … and information systems, 2012 - Springer
Given a network of who-contacts-whom or who-links-to-whom, will a contagious
virus/product/meme spread and 'take over'(cause an epidemic) or die out quickly? What will …

Influence maximization in dynamic social networks

H Zhuang, Y Sun, J Tang, J Zhang… - 2013 IEEE 13th …, 2013 - ieeexplore.ieee.org
Social influence and influence diffusion has been widely studied in online social networks.
However, most existing works on influence diffusion focus on static networks. In this paper …