Article
Computer Science, Information Systems
Marc Serramia, Maite Lopez-Sanchez, Stefano Moretti, Juan A. Rodriguez-Aguilar
Summary: Decision makers face challenges in comparing and ranking elements based on multiple criteria and personal preferences. This study introduces a new decision-making framework and presents a new method for ranking single elements. It is also proven that the contributions of this study generalize recent results in the field of social choice. The findings are illustrated through a case study on ethical decision-making.
INFORMATION SCIENCES
(2023)
Article
Clinical Neurology
Hui Xie, Licheng Mo, Sijin Li, Jialin Liang, Xiaoqing Hu, Dandan Zhang
Summary: Individuals with depressive symptoms exhibit attentional bias towards negative social feedback and diminished response to highly positive feedback, which further influences their memory, social evaluation, and social decision-making. These findings highlight the importance of targeting these aberrant biases in preventing the development of major depressive disorders.
JOURNAL OF AFFECTIVE DISORDERS
(2022)
Letter
Medicine, General & Internal
Laura J. Faherty, Gerald P. Hunter, Pierrce Holmes, Jeanne S. Ringel
Summary: This survey study investigates the usage of incentives for COVID-19 vaccination and explores how different sociodemographic factors are associated with individuals' opinions on the impact of incentives on trust in the COVID-19 vaccine.
Article
Computer Science, Artificial Intelligence
J. Ignacio Serrano, Angel Iglesias, Steven P. Woods, M. Dolores del Castillo
Summary: This study examines a novel computational cognitive model of the Iowa Gambling Task (IGT) that captures fine-grained differences in decision-making styles in individuals with recent methamphetamine use disorders. The models generated from the study are more sensitive than traditional metrics in detecting risky decision-making behaviors in persons with methamphetamine use disorders. Methamphetamine users exhibit lower estimation of possible losses and associated risk, while multi-substance users show behavior patterns that affect the evaluation of losses and the risk associated with gains.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics, Interdisciplinary Applications
Xuelian Ni, Fei Xiong, Shirui Pan, Hongshu Chen, Jia Wu, Liang Wang
Summary: In this study, the pattern of heterogeneous social influence on human decision-making from the perspectives of opinions, behaviors, preferences, and decision probabilities is investigated across three large-scale online networks. The results show that similar behavior during exploration has a stronger influence on decision-making compared to explicit social relationships, regardless of relationship sparsity, and is associated with shared experiences, network structures, and individual attributes.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Management
Jan Hazla, Ali Jadbabaie, Elchanan Mossel, M. Amin Rahimian
Summary: The study shows that computations performed by Bayesian agents in opinion exchange over a network are NP-hard, particularly for binary actions and revealing posterior beliefs. Additionally, even approximating Bayesian posterior beliefs is challenging.
OPERATIONS RESEARCH
(2021)
Article
Neurosciences
Yonglin Lin, Ruolei Gu, Jiali Zhou, Yiman Li, Pengfei Xu, Yue-jia Luo
Summary: The study found that social information can impact decision-making, with Social Misalignment Sensitivity and egocentric tendency playing important roles in this process. Different brain regions were activated in socially aligned and misaligned situations, indicating variations in the monitoring system's scope. The dorsolateral prefrontal cortex may selectively interact with SMS in individuals with a low switching threshold, suggesting sensitivity to inter-individual variation.
Article
Management
Johannes Ulrich Siebert, Reinhard E. Kunz, Philipp Rolf
Summary: Decision sciences emphasize the importance of decision training, but few studies have empirically tested its effectiveness or practical usefulness, and even fewer have investigated its impact on problem structuring. Effective structuring of problems and generating alternatives is crucial in decision-making processes, leading to increased decision satisfaction and overall life satisfaction. Research findings indicate positive effects of decision training on proactive cognitive skills and decision satisfaction, with minimal impact on proactive personality traits and limited significant interactions with experience.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Information Systems
Youfang Leng, Li Yu, Xi Niu
Summary: The rapid development of social networks has made group activities part of people's daily lives. Recent research has focused on group recommendations and adopted deep neural networks to model the process of group decision-making. This paper proposes a novel group recommendation framework that dynamically aggregates social influence diffusion and interest evolution to address the challenges in individual preference learning and group decision-making phases.
INFORMATION SCIENCES
(2022)
Article
Clinical Neurology
Shinsuke Suzuki, Yuichi Yamashita, Kentaro Katahira
Summary: This study found that a trans-diagnostic dimension of psychiatric symptoms related to compulsive behavior and intrusive thought was negatively correlated with overall decision-making performance in both reward-seeking and loss-avoidance tasks. Further analysis revealed that this psychiatric dimension was associated with lower preference for options that recently led to better outcomes in both tasks. These findings suggest that psychiatric symptoms influence decision-making processes for seeking rewards and avoiding losses through both common and distinct computational processes.
PSYCHIATRY AND CLINICAL NEUROSCIENCES
(2021)
Article
Business
Vera Ferron-Vilchez, Jesus Valero-Gil, Ines Suarez-Perales
Summary: Greenwashing is a communication practice where firms disclose environmentally misleading information, and this study empirically examines how it influences managers' decision-making, as well as the moderating effect of environmental management attitude in this relationship. This research is based on experimental design.
CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT
(2021)
Article
Psychology, Clinical
Tiejun Kang, Yi Zhang, Jing Zhao, Xiaoyan Li, Heng Jiang, Xiaotong Niu, Renqian Xie, Xiaobin Ding, Vaughn R. Steele, Ti-Fei Yuan
Summary: This study found that male individuals with heroin use disorder exhibit changes in multi-dimensional impulsivity, distinguishing them from healthy controls and predicting clinical severity.
INTERNATIONAL JOURNAL OF MENTAL HEALTH AND ADDICTION
(2022)
Article
Automation & Control Systems
Yangjingjing Zhang, Xia Chen, Witold Pedrycz, Yucheng Dong
Summary: This article addresses the key issues of weight determination and consensus reaching in social network group decision making (SNGDM). By establishing a model for social influence evolution and designing a consensus reaching process based on social influence evolution (CRP-SIE), the article proposes a method to assist individuals in reaching consensus in SNGDM. Simulation analysis is conducted to investigate the effects of social influence evolution on consensus reaching, and the advantages of the proposed method are demonstrated through comparative analysis.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Green & Sustainable Science & Technology
Vaclav Beran, Marek Teichmann, Frantisek Kuda
Summary: This paper discusses how problems faced by decision-makers can escalate under various influences, emphasizing the complexity and chaos of processes in technical and economic structures. It explores the possibility of choosing the right time and place for process activities and illustrates the positive impact of such decision-making.
Article
Psychology, Clinical
Anna-Lena Frey, Michael J. Frank, Ciara McCabe
Summary: Individuals with depression show lower social learning rates and reduced quality and quantity of everyday social experiences, especially spending more time in negative social situations, which may negatively impact real-life social interactions.
PSYCHOLOGICAL MEDICINE
(2021)
Article
Automation & Control Systems
Yang Liu, Zhonglei Gu, Tobey H. Ko, Jiming Liu
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Automation & Control Systems
Qing Cai, Sameer Alam, Jiming Liu
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2020)
Article
Engineering, Multidisciplinary
Qing Cai, Mahardhika Pratama, Sameer Alam, Chunyao Ma, Jiming Liu
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2020)
Article
Computer Science, Artificial Intelligence
Qi Tan, Yang Liu, Jiming Liu
Summary: This article presents a comprehensive framework for deep learning model design and information-theoretic analysis, including an interactive and integrative connected deep recurrent neural network ((IDRNN)-D-2) model and information-theoretic analysis to prove the model's learning capacity. Through a series of experiments, the model performs well in various data sets and PSTA tasks, capturing multiscale spatiotemporal dependencies.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jiaxu Cui, Bo Yang, Bingyi Sun, Xia Hu, Jiming Liu
Summary: We propose a general and scalable global optimization framework that uses a Bayesian graph neural network to approximate expensive objectives. This method avoids the complexity issues of Gaussian processes and scales linearly with the number of observations. Strict theoretical support is provided for its convergence. Intensive experiments on various problems demonstrate its effectiveness compared to the current state of the art.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Information Systems
Haiqiang Wang, Yinying Wu, Chao Gao, Yue Deng, Fan Zhang, Jiajin Huang, Jiming Liu
Summary: This paper presents a new medication combination prediction model, TAMSGC, based on the temporal attention mechanism and simple graph convolution, which outperforms baseline models in predicting medication combinations with higher accuracy.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Automation & Control Systems
Qing Cai, Sameer Alam, Mahardhika Pratama, Jiming Liu
Summary: This article explores the robustness of multipartite networks under node failures and proposes a generic percolation theory for evaluating their robustness. The experiments demonstrate a good agreement between simulation results and the proposed theory.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xuliang Zhu, Xin Huang, Longxu Sun, Jiming Liu
Summary: This article investigates the problem of potential transmission cluster discovery based on spatio-temporal logs. Two indexing algorithms, a multigraph index and an advanced BCG-index, are proposed to improve the efficiency of discovering potential transmission clusters.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2023)
Article
Engineering, Multidisciplinary
Xianghua Li, Xin Qi, Xingjian Liu, Chao Gao, Zhen Wang, Fan Zhang, Jiming Liu
Summary: Recently, the issue of complex network clustering has gained great attention, with optimization algorithms targeting multiple objectives showing potential in overcoming limitations of single-objective optimization. However, a key drawback is the inability to effectively balance exploration and exploitation. To address this, a new method called multi-objective discrete moth-flame optimization (DMFO) is proposed, which demonstrates high efficiency in handling complex network division challenges through synthetic and real-world network experiments.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Dong Li, Wenbo Song, Jiming Liu
Summary: Complex network models are foundational in explaining the rules behind network structure evolution and are crucial for understanding and controlling complex networks. Existing studies have not fully captured the internal mechanisms of community emergence and evolution in networks. To address this limitation, we propose a Reaction-Diffusion model based on Q-Learning technology (RDQL), which treats each node as an intelligent agent making behavior choices to update relationships. Extensive experiments demonstrate that our model reveals community formation and evolution, and generates networks with properties such as scale-free, small-world, and assortativity. The RDQL model's effectiveness is further validated through real network applications. Additionally, our in-depth analysis shows that the proportion of exploration and exploitation behaviors is the sole factor affecting community formation. The RDQL model holds potential as a fundamental tool for studying network stability and dynamics.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Automation & Control Systems
Jinfu Ren, Yang Liu, Jiming Liu
Summary: Subspace learning is crucial for learning tasks with a large feature space. Existing multitask methods focus on the commonality among tasks and neglect the individuality. This article proposes a novel method, CISL, which considers both commonality and individuality, and demonstrates its effectiveness through experiments.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Engineering, Multidisciplinary
Benyun Shi, Jianan Zhong, Hongjun Qiu, Qing Bao, Kai Liu, Jiming Liu
Summary: This paper focuses on a hybrid network embedding problem that aims to simultaneously preserve both structural proximity and equivalence of network nodes. By introducing the concept of graphlet degree vector (GDV) and implementing cross-layer random walk methods, the proposed approach shows superior performance in tasks such as node clustering, node classification, and label prediction on both synthetic and real-world datasets.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
Chunpeng Zhou, Benyun Shi, Hongjun Qiu, Jiming Liu
Article
Engineering, Multidisciplinary
Qing Cai, Jiming Liu
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2020)
Article
Computer Science, Information Systems
Hechang Chen, Bo Yang, Jiming Liu, Xiao-Nong Zhou, Philip S. Yu
