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IEEE Technology Navigator

IEEE Technical Community Spotlight

Transactions on Computational Social Systems

Scope

IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. “Systems” include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.

Learn more and submit your paper today.

Posting Preprints to Non-IEEE Servers

Authors should disclose postings on approved preprint services when submitting papers to SMCS Journals.

Consult relevant sections posted here.

The following statement must be included on the initial screen of the preprint site:

  • “This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.”

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Editor-in-Chief

Bin Hu
Bin Hu
Editor-In-Chief

Gansu Provincial Key Laboratory of Wearable Computing

School of Information Science and Engineering, Lanzhou University

Lanzhou, China

Email: [email protected]

REQUEST TO UPDATE CONTENT BOOKMARK PAGE

 

Peer Review

The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE Publication Services and Products Board Operations Manual. Each published article was reviewed by a minimum of two independent reviewers using a single-anonymous peer review process, where the identities of the reviewers are not known to the authors, but the reviewers know the identities of the authors. Articles will be screened for plagiarism before acceptance.

Editorial Board Members

  • HUSSEIN ABBASS, Univ. of New South Wales, Australia
  • MOUSA AL-KFAIRY, Zayed Univ., UAE
  • SAMBIT BAKSHI, Nat. Inst. of Tech. Rourkela, India
  • KRISHAN BERWAL, Military College of Telecommunication Engineering, India
  • DANIEL BILAR, Norwich Univ., United States
  • HANSHU CAI, Lanzhou Univ., China
  • WEI CAI, Univ. of Washington, United States
  • ZHIPENG CAI, Georgia State Univ., United States
  • GABRIELLA CASALINO, Univ. of Bari Aldo Moro, Italy
  • LONG CHEN, WAYTOUS, China
  • XUEQI CHENG, Chinese Academy of Sci., China
  • ZHIYONG CHENG, ZhongJuYuan Intelligent Tech. Co., Ltd., China
  • PETER CHIN, Boston Univ., United States
  • CARMELA COMITO, Consiglio Nazionale delle Ricerche (CNR), Italy
  • GEORGE CYBENKO, Dartmouth College, United States
  • DEBASMIT DAS, QUALCOMM Inc., United States
  • GAURAV DHIMAN, Jagat Guru Nanak Dev Punjab State Open Univ., India
  • YOUCEF DJENOURI, Univ. of South-Eastern, Norway
  • QUNXI DONG, Beijing Inst. of Tech., China
  • WEI DUAN, National Univ. of Defense Tech., China
  • MARIA PIA FANTI, Politecnico di Bari, Italy
  • LUOYI FU, Shanghai Jiao Tong Univ., China
  • MARINA L. GAVRILOVA, Univ. of Calgary, Canada
  • HANSU GU, Amazon.com Inc., United States
  • SAQIB HAKAK, Univ. of New Brunswick, Canada
  • RICHANG HONG, Hefei Univ. of Tech., China
  • XIPING HU, Bravolol Limited, China
  • ROY KA-WEI LEE, Singapore Univ. of Tech. and Design, Singapore
  • VICTOR C.M. LEUNG, Univ. of British Colombia, Canada
  • JUANJUAN LI, Beijing Inst. of Tech., China
  • KEN LI, Univ. College London, United Kingdom
  • LINGXI LI, Indiana Univ., United States
  • MI LI, Beijing Univ. of Tech. China
  • XUERONG LI, Chinese Acad. of Sci., China
  • GUANJUN LIU, Tongji Univ. China
  • XIAOFAN LIU, City Univ. of Hong Kong, China
  • YU LIU, South China Univ. of Tech., China
  • ZHE LIU, Zhejiang Lab, China
  • ZHIHAN LV, Uppsala Univ., Sweden
  • KENJI MORITA, The Univ. of Tokyo, Japan
  • NURIA OLIVER, Vodafone, United Kingdom
  • VIR PHOHA, Syracuse Univ., United States
  • RUI QIN, Chinese Academy of Sciences, China
  • IMRAN RAZZAK, Deakin Univ., Australia
  • RAJA. S.P., VelTech Univ., India
  • SRIPARNA SAHA, Indian Inst. of Tech. Patna, India
  • YINGYING SHE, Xiamen Univ., China
  • KAIZE SHI, Univ. of Tech. Sydney, Australia
  • AMIT KUMAR SINGH, Nat. Inst. of Tech. Patna, India
  • Krishna Kant Singh, Delhi Technical Campus of GGSIPU, India
  • DAWEI SONG, The Open Univ. (OU), United Kingdom
  • GAUTAM SRIVASTAVA, Brandon Univ., Canada
  • YING TANG, Rowan Univ., United States
  • ZHE WAN, National Development and Reform Commission, China
  • FEI-YUE WANG, Chinese Academy of Sci., China
  • SHIQIANG WANG, Thomas J. Watson Research Center, United States
  • TAO WANG, National Univ. of Defense Tech., China
  • XIAO WANG, Qingdao Academy of Intelligent Industries, China
  • KEVIN XU, Univ. Toledo, United States
  • DONGREN YAO, Harvard Medical School, United States
  • PEIJUN YE, Chinese Academy of Sci., China
  • HUI YU, Univ. of Glasgow, United Kingdom
  • JUN JASON ZHANG, Univ. of Denver, United States
  • LIYING ZHANG, Central Univ. of Finance and Economics, China
  • QINGPENG ZHANG, Univ. of Hong Kong, China
  • SUNSHINE ZHANG, Duke Kunshan Univ., China
  • TONG ZHANG, South China Univ. of Tech., China
  • MIN ZHOU, Beijing Jiaotong Univ., China
  • XIAOKANG ZHOU, Kansai Univ., Japan
  • HAIBIN ZHU, Nipissing Univ., Canada
  • JIA ZHU, Zhejiang Normal Univ., China
  • JIANMING ZHU, Univ. of Chinese Academy of Sci., China

 

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Converging Real and Virtual: Embodied Intelligence-Driven Immersive VR Biofeedback for Brain Health Modulation
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Sandwich arbitrage is a popular strategy for blockchain-based decentralized exchange (DEX) users to facilitate decentralized token exchanges and make profits. However, conventional Sandwich arbitrage only focuses on one big-deal transaction and executes arbitrary actions within an intrablock, leading to a huge loss of profit opportunities. In this article, we present...
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Detecting social media bots has become increasingly critical due to their detrimental impact on online environments. With the emergence of sophisticated large language models (LLM) such as ChatGPT, bot detection faces new challenges. These bots based on LLMs exhibit human-like behaviors, and it is difficult for traditional detection approaches to...
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Understanding DAOs: An Empirical Study on Governance Dynamics
As a typical instance of human–computer interaction, the notion of decentralized autonomous organization (DAO) represents an organization constructed by automatically executed rules, such as via smart contracts, incorporating features of the permissionless committee, transparent proposals, and fair contributions by stakeholders. As of May 2023, DAO has impacted over $24.3B market...
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Graph-Based Methods for Multimodal Indoor Activity Recognition: A Comprehensive Survey
This survey article explores graph-based approaches to multimodal human activity recognition in indoor environments, emphasizing their relevance to advancing multimodal representation and reasoning. With the growing importance of integrating diverse data sources such as sensor events, contextual information, and spatial data, effective human activity recognition methods are essential for applications...

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