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Article
A polyhedral approach to least cost influence maximization in social networks
The least cost influence maximization problem aims to determine minimum cost of partial (e.g., monetary) incentives initially given to the influential spreaders on a social network, so that these early adopter...
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Article
Continuous cubic formulations for cluster detection problems in networks
The celebrated Motzkin–Straus formulation for the maximum clique problem provides a nontrivial characterization of the clique number of a graph in terms of the maximum value of a nonconvex quadratic function o...
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Article
Open AccessInfluence maximization in social media networks concerning dynamic user behaviors via reinforcement learning
This study examines the influence maximization (IM) problem via information cascades within random graphs, the topology of which dynamically changes due to the uncertainty of user behavior. This study leverage...
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Article
Open AccessInfluence network design via multi-level optimization considering boundedly rational user behaviours in social media networks
Social media networks have been playing an increasingly more important role for both socialization and information diffusion. Political campaign can gain more supporters by attracting more mass attention and i...
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Article
Open AccessNetwork-based indices of individual and collective advising impacts in mathematics
Advising and mentoring Ph.D. students is an increasingly important aspect of the academic profession. We define and interpret a family of metrics (collectively referred to as “a-indices”) that can potentially be ...
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Chapter and Conference Paper
Collective Behavior of Price Changes of ERC-20 Tokens
We analyze a network constructed from tokens developed on Ethereum platform. We collect a large data set of ERC-20 token prices; the total market capitalization of the token set is 50.2 billion ...
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Chapter and Conference Paper
Double-Threshold Models for Network Influence Propagation
We consider new models of activation/influence propagation in networks based on the concept of double thresholds: a node will “activate” if at least a certain minimum fraction of its neighbors are active and no m...
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Chapter and Conference Paper
A Cutting Plane Method for Least Cost Influence Maximization
We study the least cost influence maximization problem, which has potential applications in social network analysis, as well as in other types of networks. The focus of this paper is on mixed-integer programmi...
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Article
Open AccessGraph-based exploration and clustering analysis of semantic spaces
The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Sp...
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Article
A cutting plane method for risk-constrained traveling salesman problem with random arc costs
In this manuscript, we consider a stochastic traveling salesman problem with random arc costs and assume that the travel cost of each arc follows a normal distribution. All the other parameters in the problem ...
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Article
Open AccessCritical Nodes in River Networks
River drainage networks are important landscape features that have been studied for several decades from a range of geomorphological and hydrological perspectives. However, identifying the most vital (critical...
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Article
Critical nodes in interdependent networks with deterministic and probabilistic cascading failures
We consider optimization problems of identifying critical nodes in coupled interdependent networks, that is, choosing a subset of nodes whose deletion causes the maximum network fragmentation (quantified by an...
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Chapter and Conference Paper
Information Network Cascading and Network Re-construction with Bounded Rational User Behaviors
Social media platforms have become increasingly used for both socialization and information diffusion. For example, commercial users can improve their profits by expanding their social media connections to ne...
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Chapter and Conference Paper
Neural Networks with Multidimensional Cross-Entropy Loss Functions
Deep neural networks have emerged as an effective machine learning tool successfully applied for many tasks, such as misinformation detection, natural language processing, image recognition, machine translatio...
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Chapter and Conference Paper
Reinforcement Learning in Information Cascades Based on Dynamic User Behavior
This paper studies the Influence Maximization problem based on information cascading within a random graph, where the network structure is dynamically changing according to users’ uncertain behaviors. The Dis...
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Chapter and Conference Paper
Ranking Academic Advisors: Analyzing Scientific Advising Impact Using MathGenealogy Social Network
Advising and mentoring Ph.D. students is an increasingly important aspect of the academic profession. We define and interpret a family of metrics (collectively referred to as “a-indices”) that can be applied to “...
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Article
A simple greedy heuristic for linear assignment interdiction
We consider a bilevel extension of the classical linear assignment problem motivated by network interdiction applications. Specifically, given a bipartite graph with two different (namely, the leader’s and the...
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Chapter and Conference Paper
Stochastic Decision Problems with Multiple Risk-Averse Agents
We consider a stochastic decision problem, with dynamic risk measures, in which multiple risk-averse agents make their decisions to minimize their individual accumulated risk-costs over a finite-time horizon. ...
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Chapter and Conference Paper
Analysis of Viral Advertisement Re-Posting Activity in Social Media
More and more businesses use social media to advertise their services. Such businesses typically maintain online social network accounts and regularly update their pages with advertisement messages describing ...
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Article
Special issue on optimization in military applications
