Co-Sponsored by IEEE Systems, Man and Cybernetics Society and IEEE Computer Society
IEEE Transaction on Computational Social Systems began publication in 2014 and welcomes paper submissions that fall within its 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 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.
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Upcoming Special Issues:
Call for Papers: Special Issue on Multimodal LLM for Elderly Diseases Discovery and Diagnosis
With the global aging population on the rise, early detection of chronic diseases in the elderly has become a pressing concern. These diseases often manifest subtly, making them difficult to diagnose promptly. Leveraging data from daily life and electronic medical records allows for the development of AI-powered tools to enhance early detection and prevention. This data includes multimodal information such as human posture, movement, facial expressions, voice, language, physiological and psychological signals, as well as electronic medical imaging and records. These techniques are widely applied in fields like computer vision, natural language processing, and cross-media computing.
Traditional research on elderly health often adopts a siloed approach, analyzing behavioral and physiological data separately. To overcome this limitation, this study aims to explore and describe human-centric multimodal data that integrates various data sources. The main research directions include: 1) Multimodal LLM-driven multimodal medical image alignment techniques that precisely align data from different modalities (such as MRI, CT scans, and genomic data) to enhance the accuracy of disease identification and diagnosis; 2) Fine-grained modeling and extraction of behavioral language and physiological signals, which involve detailed modeling of video and motion sensor data, along with voice recordings and wearable device data, to create an individual-centric human state model; 3) LLM-based techniques for aligning individual multimodal data with natural language, enabling precise cognitive assessments and personalized health recommendations for the elderly; 4) Modal identification and understanding of different data sources, ensuring effective protection of individual privacy when processing and analyzing multimodal data. By leveraging extensive multimodal datasets and designing advanced multimodal fusion models, we aim to improve the accuracy and insights in disease diagnosis, ensuring that elderly individuals continuously receive high-quality healthcare services.
This special issue aims to gather novel research works related to Multimedia Information-Based Discovery and Diagnosis for Elderly Diseases. We welcome paper submissions providing innovative results, methods, applications, and solutions-related disciplines. We believe the special issue will offer a timely collection of research updates to benefit the researchers and practitioners working in the broad multimedia, pattern recognition, and computing communities.
Topics of interest include but are not limited to:
- Application of deep learning for the prediction of health risks in the elderly population, focusing on neurological, cardiovascular, and metabolic conditions.
- Multi-modal alignment techniques for the identification and prediction of brain tumors using deep learning methods.
- High-resolution lung reconstruction using deep learning for enhanced diagnosis of pulmonary conditions.
- Cognitive assessments driven by daily activity patterns for the early detection of Alzheimer’s and other neurodegenerative diseases.
- 3D reconstruction techniques for creating detailed models of brain structures from MRI scans, facilitating improved visualization and assessment for clinical decision-making.
- Behavioral analysis of elderly health, including gait, posture, and mobility patterns, using advanced deep learning techniques.
- Machine learning-based predictions and management of blood pressure variations in elderly patients.
- Deep learning applications in retinal imaging for the early detection of ophthalmological conditions such as macular degeneration and diabetic retinopathy.
- Advanced signal processing techniques using deep learning for improved diagnosis of cardiac arrhythmias through ECG analysis.
- Super-resolution algorithms for enhancing the quality and detail of cardiovascular CT angiography images, enabling more accurate detection of plaques and vascular anomalies.
- Cross-domain data integration using deep learning for comprehensive health assessments in elderly populations.
- Integration of natural language processing and deep learning techniques for the comprehensive analysis of elderly patient records.
- Privacy-preserving methods for elderly health data using federated learning and differential privacy.
Important Dates
- Manuscript submission deadline: June 25, 2025
- Notification of acceptance: Aug 25, 2025
- Submission of final revised paper: Oct 25, 2025
- Publication of special issue (tentative): Feb, 2026
Guest Editors:
- Prof. Honghao Gao, Shanghai University, China/Gachon University, South Korea
- Prof. Muddesar Iqbal, London South Bank University, UK
- Prof. Walayat Hussain, Australian Catholic University, Australia
- Prof. Ramón J. Durán Barroso, Universidad de Valladolid, Spain
Call for Papers: Special Issue on Intelligence of Social Things-enabled Cooperative Learning for Behavioral-Cultural Modeling
Intelligence of Social Things (IoST) refers to the concept of embedding intelligence into interconnected social devices. Cooperative learning involves the collective intelligence from various sources to develop models. When applied to behavioral cultural modeling, IoST-enabled Cooperative learning uses data from social devices and platforms to collectively understand and model behavioral and cultural patterns within a society. The integration of AI, social networks, IoT, Cooperative learning, and behavioral cultural modeling represents a multidisciplinary approach. This integrated approach has the potential to offer comprehensive insights into societal behaviors, cultural dynamics, and community interactions, enabling the development of targeted interventions, policies, and technologies to address various social and cultural challenges. Social transparency in Cooperative learning for behavioral cultural studies entails creating an environment where participants openly share information, insights, and experiences related to behavioral and cultural aspects. This approach fosters an atmosphere of openness, trust, and knowledge sharing, enabling the collective understanding and analysis of behavioral and cultural dynamics. It encourages active participation, diverse perspectives, and the exchange of insights to deepen the study of behavioral and cultural patterns within a Cooperative learning setting. Social learning performance in the context of IoT involves leveraging interconnected devices and systems to enhance Cooperative learning experiences. This could include using IoT devices to facilitate real-time data sharing, interactive learning tools, and personalized feedback, ultimately improving the overall effectiveness and efficiency of social learning environments. Utilizing IoT in social learning can lead to more dynamic, interactive, and tailored learning experiences, fostering greater engagement and knowledge retention among participants. The Intelligence of Social Things platforms provides the necessary infrastructure for managing, analyzing, and visualizing socially implanted behavioral cultural data, enabling social providers to make informed decisions and improve patient care. Intelligence of Social Things security and privacy are paramount considerations for social applications.
Topics include but are not limited to:
- IoST-enabled behavioral cultural systems.
- Application of cooperative learning techniques in analyzing IoST data and identifying potential issues
- Social Transparency in collaborating learning
- Sociocultural Perspectives of Cooperative learning
- Social learning performance for IoST
- IoST-driven behavioral cultural modeling and management platforms.
- Development of IoST-based algorithms for behavioral cultural recommendations and optimization
- IoST-enabled mental health monitoring and intervention tools.
- Application of cooperative learning algorithms to analyze IoST data and detect early signs of mental health issues.
- IoST-based wearable devices and sensors for comprehensive social data collection.
- IoST platforms and architectures for efficient data management, analysis, and visualization.
- Robust IoST security and privacy solutions to safeguard sensitive social data.
- Ethical frameworks and regulations governing the responsible use of IoST in social care.
- IoST and multi-modal data analysis using cooperative learning
- Security of IoST devices and platforms
Important Dates:
- Submissions Deadline: March 30, 2025
- First Reviews Due: June 15, 2025
- Revision Due: September 01, 2025
- Acceptance Notification: November 1, 2025
- Final Manuscript Due: November 15, 2025
- Publication Date: December 2025
Guest Editors:
- Chinmay Chakraborty, Birla Institute of Technology, Mesra, India (Corresponding)
- Bhuvan Unhelkar, University of South Florida, USA
- Saïd Mahmoudi, University of Mons, Belgium
- Martin Margala, University of Louisiana at Lafayette, USA
- Guangjie Han, Hohai University, China
- Suman Ghosh, Finland Research Centre Huawei, Finland
- Sayonara Barbosa, University of Cincinnati, USA
Call for Papers: Special Issue on Emotion AI and Sentiment Analysis in Social Systems
The advent of Emotion AI and sentiment analysis represents a significant leap forward in the field of computational social systems, offering profound implications for how we understand and interact with human emotions in digital environments. As digital interactions become increasingly prevalent, the ability to accurately detect, interpret, and respond to human emotions through artificial intelligence has emerged as a critical area of research. This special issue aims to explore the transformative potential of these technologies in enhancing social systems, improving user experiences, and addressing societal challenges.
Emotion AI and sentiment analysis involve the use of machine learning algorithms, natural language processing, and advanced data analytics to assess emotional states from textual data, voice intonations, facial expressions, and physiological signals. These technologies enable the development of systems that can understand and respond to human emotions in real-time, offering a wide range of applications across various domains. In customer service, Emotion AI can lead to more empathetic and effective interactions, thereby increasing customer satisfaction and loyalty. In mental health, these technologies can provide early detection of emotional distress and support interventions, significantly impacting patient outcomes.
Furthermore, in the educational sector, Emotion AI can personalize learning experiences by adapting content and teaching methods based on students’ emotional responses, thereby enhancing engagement and academic performance. In social media analysis, sentiment analysis can offer insights into public opinion, societal trends, and the emotional impact of events, aiding policymakers and businesses in making informed decisions.
Despite these promising applications, several challenges remain. The accuracy and reliability of emotion detection, ethical considerations regarding privacy and consent, and the potential for bias in AI algorithms are critical issues that need to be addressed. This special issue seeks to bring together leading researchers, practitioners, and policymakers to discuss these challenges and present cutting-edge research, innovative solutions, and practical applications of Emotion AI and sentiment analysis in social systems.
By focusing on this emerging field, the IEEE Transactions on Computational Social Systems aims to foster a deeper understanding of how emotion AI and sentiment analysis can be harnessed to create more responsive, empathetic, and effective social systems. This special issue will not only highlight the latest advancements but also inspire future research and development in this pivotal area, ultimately contributing to the betterment of society through technology.
Topics include but are not limited to:
- Development of advanced machine learning algorithms for emotion detection.
- Natural language processing methods for sentiment analysis.
- Multimodal emotion recognition combining text, voice, facial expressions, and physiological signals.
- Deep learning approaches for improving the accuracy of emotion and sentiment analysis.
- Sentiment analysis for real-time feedback and service improvement.
- Case studies on the implementation of Emotion AI in customer support systems.
- Emotion AI applications in early detection of mental health issues.
- Sentiment analysis in social media for monitoring mental health trends.
- Development of AI-driven mental health support tools and applications.
- Emotion AI for adapting educational content based on student emotions.
- Sentiment analysis in e-learning platforms to enhance student engagement.
- Case studies on the impact of Emotion AI on learning outcomes.
- Emotion AI in monitoring and mitigating the spread of misinformation.
Important Dates:
- Submissions Deadline: July 31, 2025
- First Reviews Due: September 31, 2025
- Revision Due: November 30, 2025
- Acceptance Notification: January 31, 2026
- Final Manuscript Due: March 31, 2026
- Publication Date: 2026
Submission Guidelines:
All papers are to be submitted through the IEEE’s Manuscript Central for Transactions on Computational Social Systems. Please select “Special Issue – “Emotion AI and Sentiment Analysis in Social Systems” under Manuscript Category of your submission. All manuscripts must be prepared according to the IEEE Transactions on Computational Social Systems publication guidelines.
Guest Editors:
- Dr. Gwanggil Jeon, Incheon National University, Korea, [email protected]
- Dr. Xiaochun Cheng, Swansea University, UK, [email protected]
- Dr. Abdellah Chehri, Royal Military College of Canada (RMC), Canada, [email protected]
- Dr. David Camacho, Universidad Politécnica de Madrid, Spain, [email protected]
- Dr. Feng Xia, RMIT University, Australia, [email protected]
- Dr. Joel Rodrigues, Federal University of Piauí (UFPI), Brazil, [email protected]
Call for Papers: Special Issue on Digital Innovation for the Preservation and Transmission of Cultural Heritage
Cultural heritage embodies the collective memory and identity of societies, encompassing both tangible and intangible elements that shape the unique characteristics of communities. As digital technologies evolve, new methods for preserving, interpreting, and innovating cultural heritage have rapidly emerged. For instance, digital archiving, virtual reality, and other technologies can help us preserve and immerse ourselves in the experience of engaging with cultural artifacts and practices. These technologies not only enhance preservation efforts but also promote greater public engagement with cultural heritage, encouraging broader participation in cultural narratives and practices. Ultimately, embracing these innovations can help ensure that cultural heritage remains vibrant and relevant in our rapidly changing world.
This special issue seeks to explore the intersection of digital technologies and cultural heritage, investigating how these technologies can enhance the preservation, transmission, and innovation of cultural traditions. We encourage contributions that address theoretical frameworks as well as present practical applications, case studies, and interdisciplinary approaches, showcasing the impact of computational technologies on digital innovation in cultural heritage. We aim to explore how these digital tools can foster a deeper understanding and appreciation of cultural heritage in our contemporary world. Furthermore, we seek to discover new technological pathways to expand the dimensions of cultural heritage and explore a new era in the development of cultural technologies.
We solicit high-quality original research papers on the topics including, but not limited to:
- Digital preservation techniques for cultural heritage
- Innovations in the transmission of cultural heritage through technologies
- Community involvement in the transmission and dissemination of cultural heritage
- The role of social media in the dissemination of cultural heritage
- Frameworks for sustainable development and technological practice models in cultural heritage
- Protection and transmission of cultural heritage through interdisciplinary research
- Digitalization of cultural heritage
Important Dates
- Full Paper Submission Deadline: December 20, 2024
- Notification of Acceptance: January 20, 2025
- Final Paper Submission: February 20, 2025
Guest Editor-in-Chief:
Yingqing Xu, Tsinghua University, [email protected]
Co-Guest Editor-in-Chief:
Yingying She, Xiamen University, [email protected]
Guest Editors:
Boming Su, Dunhuang Academy, [email protected]
Qingshan Zhao, Lanzhou University, [email protected]
Yunbing Chen, Tsinghua University, [email protected]
Call for Papers: Special Issue on Knowledge-Infused Learning for Computational Social Systems
Over the last decades, research on computational social systems has gained much more attention, with thousands of researchers and practitioners leveraging diverse research findings and experimental models to enrich this domain. Thanks to the digital age, which has made the computational social system a reality. However, the integration of this technology in our daily lives leads to the generation of enormous amounts of data. The scale of this data is vast, and it presents unprecedented opportunities to examine complex social behaviours, ranging from the proliferation of infectious disease to socio-economic disparity. Probably these instances were further enhanced with the associated research findings.
Guest Editors
Dr. Tu Nguyen (Lead Guest Editors)
Kennesaw State University, USA.
Email: [email protected]
Dr. Vincenzo Piuri
University of Milan, Italy
Email: [email protected]
Dr. Joel Rodrigues
Federal University of Piauí (UFPI), Teresina – PI, Brazil
Email: [email protected]
Dr. Lianyong Qi
Qufu Normal University, China.
Email: [email protected]
Dr. Shahid Mumtaz
Instituto de Telecomunicações, Portugal
Email: [email protected]
Dr. Warren Huang-Chen Lee
National Chung Cheng University, Taiwan.
Email: [email protected]
Call for papers: Special issue on AI-Driven Technologies in Social Fintech for Enhancing Sustainable Development and Social Responsibility
The rapid development of technology has brought about revolutionary changes in people’s lifestyles, notably shifting transaction modes from physical to digital. This transformation has made Financial Technology (FinTech) a highly popular topic. The rise of the digital economy enables individuals to use mobile payments, digital wallets, and invest in digital currencies or store money in online banking. The identity verification technologies required by FinTech have also been extended to borrowing services for physical objects such as books and bicycles. However, these convenient functionalities no longer satisfy people’s desires for technological advancements. Human society has begun integrating Artificial Intelligence (AI) into activities such as stock market investments, payment identification technologies, insurance, and risk assessment. These technologies are widely used and remain prominent in ongoing research.
In recent years, driven by the mainstream adoption of Sustainable Development Goals (SDGs), Social Fintech has gained increasing recognition. Compared to traditional FinTech, Social Fintech places a stronger emphasis on trust within sharing economies, social responsibility, and social interactions. Examples include P2P lending, crowdfunding, group lending, social impact investing, shared bicycles/cars, and financial education platforms. However, due to its social nature, Social Fintech faces challenges not only in the technical aspects of FinTech but also in managing social interactions, building trust, safeguarding data privacy, ensuring legal compliance, and addressing societal impacts. This multidimensional complexity requires innovative technological solutions, and platforms that support higher flexibility, operations, and management to meet user demands and ensure sustainable development. This special issue will focus on how AI technology can promote the sustainable development and social responsibility of Social Fintech. It will present specific research directions and expected outcomes aimed at generating important discussions and will influence academia and related industries.
The special issue has the following topics (but are not limited to):
- Identity verification technology in Social Fintech
- Trust and credibility in Social Fintech
- Social optimization of the sharing economy
- Blockchain-based lending mechanisms
- Design and development of financial education platforms
- Optimization of social investments portfolios
- AI model security in Social Fintech
- Sustainable applications of Social Fintech
- Transparency and optimization of digital fundraising
- AI-driven social responsibility
Important dates (tentative)
- Paper Submission Deadline: Dec. 31, 2024
- First Round of Reviews Deadline: Mar. 31, 2025
- Submission of Revision Deadline: May 31, 2025
- 2nd Round of Reviews Deadline: Jul. 31, 2025
- Decision of Acceptance Deadline: Aug. 31, 2025
Guest Editors
- Han-Chieh Chao, Tamkang University, Taiwan
- Hsin-Hung Cho, National Ilan University, Taiwan
- Sherali Zeadally, University of Kentucky, USA
- Chee Wei Tan, Nanyang Technological University, Singapore
Submission Guidelines
Authors should prepare their manuscripts according to the submission guidelines of the IEEE Transactions on Computational Social Systems. Manuscripts should be submitted through the online submission system at: https://ieee.atyponrex.com/journal/tcss, and select “Special Issue” of “AI-Driven Technologies in Social Fintech for Enhancing Sustainable Development and Social Responsibility” under the Manuscript Category. Papers recycled from those accepted at conferences cannot be considered for publication as SI in the journal. However, extended versions of papers accepted at conferences can be submitted to the journal’s SI, provided that the journal version includes a significant amount of new material. Additionally, these papers must be clearly identified by the authors at the time of submission, and a detailed explanation of the extensions made must be provided in the cover letter accompanying the submission. For any inquiries, please contact: [email protected].
Download call for special issue
Call for papers: Special Issue on Revolutionizing Social Intelligence with AI Technologies and Sensing Innovations.
The advancement of AI and sensing innovations has unveiled unprecedented opportunities to enhance social
intelligence. This evolution has not only reshaped the way we understand and interact with the social world
but has also led to innovative approaches to solving complex social challenges. The combination of artificial
intelligence, sensing technologies, and social science computing presents unparalleled opportunities to create
systems capable of comprehending, forecasting, and impacting social dynamics in more precise and efficient
manners. This special issue is dedicated to exploring the various aspects of AI and sensing
technologies-empowered social intelligence, from the collection of real-time social and environmental data
through wearable device and IoT sensors to the analysis of complex social patterns and behaviors using
advanced AI algorithms.
The special issue aims to provide a comprehensive platform to showcase research achievements that
contribute to the theory, methods, and applications of AI and sensing technology-enhanced social intelligence.
We anticipate investigating the developing trends and possibilities presented by this
interdisciplinary field to enhance our comprehension of social systems and promote the overall welfare
of global communities.
This special issue invites high-quality, original contributions from researchers,
practitioners, and technologists
working at the forefront of AI and sensing technologies applied to social intelligence. The journal encourages
the submission of articles that present the latest research results and reflect on potential research directions
and challenges in revolutionizing social intelligence with AI and sensing innovations. Additionally, extended
versions of selected high-quality papers from UIC2024, as well as notable conferences such as Ubicomp,
KDD, ICDE, AAAI, MOBICOM, SIGCOMM within the field will be invited to enrich the scope of this
special issue.
The special issue has the following topics (but are not limited to):
- AI-driven models for social behavior prediction and analysis
- Sensor-based systems for real-time social interaction monitoring
- Foundation models for social network analysis
- Data fusion methods for social applications
- Real-world applications of AI and sensing technologies in social systems
- Innovative contact or non-contact and IoT technologies for social sensing
- Computational models for social dynamics
- Crowd sensing and computing for social cognition
- Ubiquitous sensing and computing for transportation monitoring and problem-solving
- Personalized systems for social care support for vulnerable groups
- Nature-inspired social intelligent systems
Important Dates (Tentative)
- Paper Submission Deadline: March 30, 2025
- First Round of Reviews Deadline: June 15, 2025
- Submission of Revision Deadline: August 30, 2025
- 2nd Round of Reviews Deadline: October 30, 2025
- Decision of Acceptance Deadline: November 30, 2025
Guest Editors:
- Runhe Huang, Hosei University, Japan.
- Bin Guo, Northwestern Polytechnical University, China.
- Binbin Zhou, Hangzhou City University, China.
- Xin Yao,Lingnan University, HK SAR, China.
- Vincenzo Piuri, University of Milan, Italy.
Submission Guidelines
Authors should prepare their manuscripts according to the submission guidelines of the IEEE Transactions on
Computational Social Systems. Manuscripts should be submitted through the online submission system at:
https://ieee.atyponrex.com/journal/tcss, and select “Special Issue” of “Revolutionizing Social Intelligence
with AI and Sensing Innovations” under the Manuscript Category. A separate cover letter should be submitted
along with your submission, and notably, if the submission is an extension of a previously published
high-quality conference paper, a detailed explanation of the significant differences should be provided. For
any inquiries, please contact: [email protected]
Download call for special issue.
Call for papers: Special Issue on Collaborative Learning and Distributed Intelligence in Cyber-Physical-Social Systems and Applications
Along with the rapid development of AI and machine learning techniques, Cyber-Physical-Social System (CPSS) now increasingly enables the intelligent human-computer interactions among human organizations, cyber networks, and physical systems through smart sensor networks associated with cloud/edge computing infrastructures. Currently, with the fundamental support of novel technologies including Artificial Intelligence of Things (AIoT) and big data analytics with large models, complex CPSS, applied in Industry 4.0, smart healthcare systems, and intelligent transportation systems, etc., leads to a promising and transdisciplinary intersection of AI, information science, and cognitive computing, etc.
In particular, distributed intelligence exploits cooperation between devices, communication infrastructures, and edge computing systems, which may optimally support CPSS by handling the distributed data independently in parallel. Collaborative learning integrates distributed learning between different peers, which can enhance CPSS to further make full use of cooperation between entities specializing in different tasks and data modalities. Therefore, the quality of CPSS-enhanced services and applications can be significantly improved from the incorporation of collaborative learning with distributed intelligence, which can efficiently manage and process heavily-loaded resources and big data mining in decentralized paradigms, toward next generation models for design and building of distributed smart applications. However, it is still facing not a few challenges, such as how to realize real-time processing as one of the fundamental requirements in communication, computation, and storage in CPSS when facing massive human-generated data every day; How to deal with the large-scale and distributed data generated by different sensors to ensure low-latency services; How to solve the heterogeneous nature and discover insightful knowledge from the multi-modality data with high-efficiency learning algorithms.
This special issue aims at: i) providing a platform for researchers and practitioners to demonstrate their novel research achievements and applications of collaborative learning and distributed intelligence in CPSS today and the foreseeable future, and ii) exploring potential research opportunities in emerging trends on the integration of physical distributed computing infrastructure, intelligent data-driven cyberspace, and human social intervention in specific application domains.
Topics of interest to this special issue include, but are not limited to:
- Collaborative learning in smart CPSS
- Distributed intelligence in end-edge-cloud systems
- Collaborative computing for smart human-machine interface design
- Multi-agent distributed system with collaborative learning
- Collaborative learning and distributed intelligence for smart manufacturing
- Collaborative learning with intelligent IoT for smart healthcare
- Big data analytics and application with collaborative learning in CPSS
- Theory and application of distributed intelligence in CPSS
- Federated learning and multi-agent reinforcement learning in CPSS
- Collaborative learning with privacy, security, and trust concerns in CPSS
Important Dates:
- Paper Submission Deadline: Dec. 31, 2024
- First Round of Reviews Deadline: Mar. 31, 2025
- Submission of Revision Deadline: May 31, 2025
- 2nd Round of Reviews Deadline: Jul. 31, 2025
- Decision of Acceptance Deadline: Aug. 31, 2025
Guest Editors:
- Xiaokang Zhou, Shiga University, Japan
- Kevin Wang, The University of Auckland, New Zealand
- Jianhua Ma, Hosei University, Japan
- Xing Li, Dongguan University of Technology, China
- Vincenzo Piuri, University of Milan, Italy
Download call for special issue
Call for papers: Special Issue on Multimodal Representation and Reasoning for Social Computing
Theme: Social computing has witnessed a significant shift towards incorporating diverse sources of information, including text, images, audio, videos, and structured knowledge graphs. The abundance of multimodal data offers valuable insights and opportunities to understand and analyze social phenomena comprehensively. However, effectively leveraging these multiple modalities requires advanced techniques for representation and reasoning. Multimodal representation needs to encode information from various modalities into a unified framework, extracting meaningful features and capturing the inherent relationships and dependencies between different modalities. Machine reasoning further incorporates complex computations, including making inferences, drawing conclusions, and understanding the underlying logic within multimodal data. These two tasks go beyond simple data fusion and require higher-level cognitive processes to extract meaningful insights from the combined modalities. Effective reasoning techniques enable us to uncover hidden patterns, detect anomalies, predict user behaviors, and gain a deeper understanding of social phenomena. By advancing the field of multimodal representation and reasoning for social computing, researchers aim to enable more accurate, comprehensive, and interpretable analysis in cyber-physical-social spaces. Eventually, the output of studies in the above areas will have significant implications across various tasks and domains, including social network analysis, affective computing, recommendation systems, e-commerce, and digital health.
Motivated by these facts, this special issue aims to enhance multimodal representation and reasoning to profoundly impact the understanding, interaction, and utilization of the potential of digital social networks. The special issue has the following topics (but are not limited to):
- Representation techniques for multimodal learning
- Semantic alignment among different modalities
- Transfer learning and domain adaptation for multimodal representation
- Cognitive-inspired multimodal representation
- Multimodal fusion techniques
- Intelligence and interpretable reasoning methods for multimodal learning
- Explainable multimodal learning models
- Graph-based reasoning for multimodal learning
- Interpretable models based on logical reasoning
- Emerging technologies (e.g., large language models) in multimodal reasoning
- Multimodal intelligent tasks, such as affective computing
- Multimodal intention and emotion recognition
- Multimodal affective fusion, generation and interaction
- Multimodal sentiment dataset and evaluation
- Cross-cultural and cross-linguistic multimodal emotional computing
- Applications of multimodal affective computing
- Multimodal applications in various fields, such as digital health
- Fusion analysis of medical image data and text data
- Multimodal medical data integration
- Multimodal remote monitoring and health management
- Multimodal assisted diagnosis and decision support
- Survey, fairness, accountability and ethics of multimodal computing
Important Dates:
- Paper Submission Deadline: July 30, 2024
- First Review Completed: September 15, 2024
- Revision Due: October 30, 2024
- Final Decision: November 15, 2024
- Publication Date: December 31, 2024
Guest Editors:
- Mengling Feng, National University of Singapore, Singapore
- Erik Cambria, Nanyang Technological University, Singapore
- Qika Lin, National University of Singapore, Singapore
- (Corresponding Editor, Email: [email protected])
- Kaize Shi, University of Technology Sydney, Australia
- Weiping Li, Peking University, China
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Call for Papers: Special Issue on Large-Scale Knowledge Discovery in Computational Social Systems
Over the last decade, significant progress has been made in understanding the inherent dynamics of social systems. In the current digital era, where each social interaction leaves a digital trace, computational modeling has proven instrumental in untangling the complexities of human behavior, collective dynamics, and societal evolution. This ever-changing landscape of social systems is continuously unfolding, playing a vital role in deciphering the intricate nature of interactions, especially in the domain of large-scale knowledge discovery. Large-scale knowledge discovery within social systems, facilitated by computational models, offers unprecedented advantages. The sheer volume and diversity of data generated in contemporary social interactions provides an expansive canvas for exploration. Leveraging large-scale datasets allows for more comprehensive insights into behavioral patterns, societal trends, and emergent phenomena, fostering a deeper understanding of the complexities inherent in social dynamics.
Nevertheless, this shift toward large-scale knowledge discovery also reveals research gaps. The challenges lie in efficiently harnessing, processing, and deriving meaningful insights from vast and diverse datasets. The adaptability of existing computational models may lag behind the dynamic nature of large-scale social interactions, necessitating efforts to bridge the divide between potential advantages and current limitations. This special issue aims to facilitate a comprehensive exploration of large-scale knowledge discovery through innovative advancements in computational modeling tailored to the intricate dynamics of contemporary social systems. The goal is to advance the field, offering a nuanced understanding of the opportunities and limitations inherent in large-scale knowledge discovery within the complex tapestry of social systems.
This special issue invites original research papers, reviews, and case studies that delve into, but are not limited to, the following topics, with a specific emphasis on large-scale knowledge discovery:
- Agent-based modeling of social interactions
- Network analysis and graph theory applications
- Machine learning and artificial intelligence methodologies for large-scale knowledge discovery
- Dynamics of opinion formation and diffusion in large-scale social networks
- Computational models elucidating cultural evolution in large-scale societies
- Simulation of collective behavior to unravel emergent phenomena in complex social systems
- Applications of computational models in decision-making with a focus on large-scale knowledge discovery
- Innovations in Large-Scale Knowledge Discovery
Important Dates:
- Manuscript submissions due: January 1, 2025
- First round of reviews completed: April 1, 2025
- Revised manuscripts deadline: June 1, 2025
- Second round of reviews completed: July 15, 2025
- Final manuscripts deadline: August 15, 2025
Guest Editors:
- Man-Fai Leung, Anglia Ruskin University, Cambridge, UK, [email protected]
- Shiping Wen, University of Technology Sydney, Australia, [email protected]
- Wenqi Fan, The Hong Kong Polytechnic University, Hong Kong, China, [email protected]
- Tingwen Huang, Texas A&M University at Qatar, Qatar, [email protected]
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Call for Papers: Special Issue on “Trends in Social Multimedia Computing: Models, Methodologies, and Applications”
Along with the fast development of high-speed networks and advanced wearable and intelligent devices, a large number of multimedia contents are now widely used by social networking sites and content-sharing services as information carriers for various applications. The integration of multimedia and social media, which we call social multimedia, supports new types of user interaction. Motivated by the tremendous growth of social media applications, social computing has emerged as a novel computing paradigm that involves studying and managing social behaviour and organizational dynamics to produce intelligent applications. However, the wide prevalence of social multimedia poses a significant challenge for social computing because many new issues involving social activity and interaction around multimedia must be addressed in a media-specific manner. Nevertheless, multimedia research still remains open, given the challenging nature of this area’s research focus. Social multimedia can help improve existing multimedia applications, so the term social multimedia computing to denote the more focused multidisciplinary research and application field between social sciences and multimedia technology.
Motivated by these facts, this special issue targets the researchers from both academia and industrial to explore and share new ideas, models, methodologies, theories and practices with focus on social multimedia computing perspectives for emerging applications.
Topics of interest include, but are not limited to:
- Social mining and prediction
- Network representation learning, GNN, and applications
- Role of artificial intelligence, machine/deep learning in social media applications
- NLP in social media
- Multi-media and social media
- Visualization in social media
- Computational social sciences
- Multimedia computing and social networks for use in real-world applications
Important Dates:
- Paper Submission Deadline: August 31, 2024
- First Review Completed: November 1, 2024
- Revision Due: January 1, 2025
- Second Review completed: February 15, 2025
- Final Manuscript Due: March 15, 2025
Guest Editors:
- Amit Kumar Singh (Corresponding Editor), National Institute of Technology Patna, India, [email protected]
- Jungong Han, University of Sheffield, UK, [email protected]
- Stefano Berretti, University of Florence, Florence, Italy, [email protected]
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Special Issue on Few-shot/Zero-shot Learning for Knowledge Discovery in Social Networks
In the era of digital connectivity and social media, social networks have become massive repositories of information and interactions among individuals. These interactions encompass a wide array of topics, from personal interests and social relationships to discussions about events, products, and more. Extracting meaningful insights and knowledge from such vast and heterogeneous data is a challenge that traditional methods struggle to address. The necessity for “Few-shot/Zero-shot Learning for Knowledge Discovery in Social Networks” arises from the limitations of conventional techniques in dealing with the unique characteristics of social network data. The traditional approaches often require labeled training data and predefined categories, which may not be feasible in the context of evolving, dynamic, and unstructured social network data. This is where Few-shot/Zero-shot learning becomes highly relevant.
Guest Editors:
- Junyang Chen, Shenzhen University, China
- Jingcai Guo, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Huan Wang, Huazhong Agricultural University, China
- Zhenghua Xu, Hebei University of Technology, China
- Mengzhu, Wang, Hefei University of Technology, China
- Nan Yin, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates
- Victor C.M. Leung, Shenzhen University / The University of British Columbia, China / Canada
Submissions for this issue will close on December 28, 2024
Download the Call for Special Issue(PDF)
IEEE Transactions on Computational Social Systems Call for paper for Special Issue on Music Intelligence and Social Computation
With the rapid development of computing technology, music intelligence has become an important research field of social computing, not only as an important direction of academic research but also as a technological impetus to subvert the music industry, with broad research space and significant application value. Realizing music intelligence by using music data as the carrier through the use of new-generation computing methods such as big data, big models, bioinformatics, and artificial intelligence technologies is an important development direction of social computing. However, due to the cross-modal characteristics of music data and the complexity of music perception and cognition, the field has great research challenges and difficulties, especially around key issues such as the mechanism of music’s regulation of human emotions, the impact of music on social behavior, the cognitive behavior of music, complex music information processing, cross-modal music information processing, etc. Consequently, there is an urgent need to further promote research in this field. Meanwhile, music intelligence has a broad and significant application prospect in the direction of music therapy, music perception, music composition, music production, etc., which can promote the development of social computing technology and realize industrial empowerment and upgrading. Therefore, exploring the industry applications of music intelligence and social computing also has high research urgency and great research significance.
The special issue will focus on the following topics:
- Research on music’s regulation on brain, recognition and human emotions
- Research on music’s influence on social groups and social behavior
- Interdisciplinary research of computational music with brain science, neuroscience, and psychology
- Novel computational music datasets, models, tasks, and evaluation methods
- Research on music therapy technologies and clinical applications for emotion disorders.
- Quantitative analysis theories and technologies for music data
- Research of computational music composition, music production, music perception and aesthetics.
- Novel industry applications, industry standards, and prototype systems for computational music
- Research on cross-modality modeling for music data with brain recognition
Submission Procedure
Manuscripts (2-column is required) should be submitted electronically through the IEEE online system according to the IEEE Transactions on Computational Social Systems journal guidelines and layout specifications.
Important Dates
- Paper Submission Deadline: March 1, 2024
- First Review Completed: June 15, 2024
- Revision Due: September 30, 2024
- Second Review Completed: November 15, 2024
- Final Manuscript Due: December 31, 2024
Guest Editors
- Xiaohong Guan, Xi’an Jiaotong University
- [email protected]
- Xiaobing Li, Central Conservatory of Music
- [email protected]
- Björn W. Schuller, Imperial College London, UK
- [email protected]
- Xinran Zhang, Central Conservatory of Music
- (Corresponding Editor) [email protected]
Special Issue on Social Manufacturing after ChatGPT
Social Manufacturing (SM), one of the emerging and fast-growing technologies, has attracted attention from academic and industry experts around the world. AI-powered intelligent manufacturing and personalization are becoming prevalent. Interesting research on SM has been conducted and shows promising application potential in the manufacturing fields. This special issue is expected to explore a wide range of topics related to SM including the connation and concept architecture of SM, advanced information and AI technologies for SM, and application verification of SM in real industrial scenarios.
Guest Editors:
- Fei-Yue Wang, Institute of Automation, Chinese Academy of Sciences, China
- Pingyu Jiang, Xi’an Jiaotong University, China
- Gang Xiong, Institute of Automation, Chinese Academy of Sciences, China
- MengChu Zhou, New Jersey Institute of Technology, USA
- Bernd Kuhlenkötter, Ruhr-Universität Bochum, GermanyPetri Helo, University of Vaasa, Finland
- Zhen Shen, Cloud Computing Center, Chinese Academy of Sciences, China
Submissions for this issue will close on January 1, 2024
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Special Issue on Interpretability and Explainability of Sentimental Analysis based on Social Media Platforms
By leveraging information from social media platforms and using artificial intelligence-based models, it is possible to make very accurate predictions for the sentimental analysis. However, for a model to classify data into different sentiment categories, it must have some knowledge of the intrinsic characteristics of the data as well as the representations of those characteristics. Most of the currently available models do not explain the reasons behind the process by which judgments are made. In this special issue, our goal is to strengthen the link between the field of sentimental analytics and AI-driven models (e.g., XAI), especially in terms of their interpretability and explainability.
Guest Editors:
- Jerry Chun-Wei Lin, Western Norway University of Applied Sciences, Norway
- Gautam Srivastava, Brandon University, Canada
- Jhing-Fa Wang, National Cheng Kung University, Taiwan
Submissions for this issue will close on November 30, 2023
Download the Call for Special Issue (PDF).
Special Issue on Social Innovation & Governance: Towards the Sustainable Digital Nation
During the past three decades, ‘social innovation’ has been increasingly gaining importance in social science research, and even more so, in practice, as our world has become increasingly interconnected due significant global challenges such as climate change, the Internet of things, sustainability, and global governance. Social and digital innovation and transformation have become key drivers for mitigating those challenges. To fully realize their potential, governance provisions need to be in place to support its dissemination across scope and scale.
Guest Editors:
- Saade, George Raafat, Beijing Institute of Technology, China
- Hao, Liu, Beijing Institute of Technology, China
- Hong, Guan, Beijing Institute of Technology, China
- Jun, Zhang, Beijing Institute of Technology, China
- Vahidov, Rustam, Concordia University, Canada
- Lahmiri, Salim, Concordia University, Canada
Submissions for this issue will close on March 31, 2023
Download the Call for Special Issue (PDF).
Special Issue on Big Data and Computational Social Intelligence for Guaranteed Financial Security
Digital finance has greatly facilitated people’s lives, accelerated the circulation of capital in various fields, and enhanced the vitality of financial markets. However, it exposes many increasing risks and hidden dangers, such as stock volatility, trading fraud, privacy leakage, etc. In addition, the storage security and high-performance computing of financial big data also faces challenges. This special issue aims to explore a wide range of issues related to financial security, paying close attention to digital currency, blockchain, fraud detection and control, secure storage and high-performance computing technologies, as well as other related studies and applications, especially with the help of AI technology.
Guest Editors:
- Changjun Jiang (Lead GE), Tongji University, China
- Fei-Yue Wang, Chinese Academy of Sciences, China
- Mengchu Zhou, New Jersey Institute of Technology, USA
- Asoke K. Nandi, Brunel University London, UK
- Guanjun Liu, Tongji University, China
Submissions for this issue will close on October 31, 2022
Download the Call for Special Issue (PDF).
Special Issue on Dark side of the Socio-Cyber World: Media Manipulation, Fake News, and Misinformation
This special issue seeks high-quality and original contributions that advance the concept, methods, and theories by going insight into the dark side of the online information and address the mechanism and strategies to overcome the root cause of fake new through Artificial Intelligence (AI) and Deep Learning (DL). Thanks to the latest innovation in Artificial Intelligence and Deep Learning, which gives deeper knowledge based on previous history. Therefore, keeping the view of the latest innovations, we believe that this is a topic of challenges faced by multidisciplinary, i.e., computer science, marketing, management, biological science, etc.
Guest Editors:
- Gwanggil Jeon, Incheon National University, South Korea
- Xiaochun Cheng, Middlesex University London, UK
- Abdellah Chehri, Université du Québec à Chicoutimi, Canada
- Giancarlo Fortino, University of Calabria, Italy
- Marcelo Albertini, University of Uberlandia, Brazil
- Shiping Wen, University of Sydney Technology, Australia
Submissions for this issue will close on March 31, 2023.
Download the Call for Special Issue (PDF).
Special Issue on Responsible AI in Social Computing
Artificial intelligence (AI) continue demonstrating its positive impact on society and successful adoptions in data rich domains including social computing systems. Responsible AI is one of the most urgent challenges of our time. There are serious ethical and legal concerns about AI’s ability to make decisions in a responsible way. Many principles and guidelines for responsible AI have been issued by governments, research organisations, and enterprises. However, high-level principles are far from ensuring the trustworthiness of AI systems. There is a significant gap between high-level principles and low-level actionable practice for developers. In this special issue, we are looking for cutting edge technologies, novel studies, and promising developments, which can improve trustworthiness of AI in social computing systems. In addition, we welcome studies using social computing to achieve responsible AI in wider AI-driven systems.
Guest Editors:
- Qinghua Lu, CSIRO, Australia
- Weishan Zhang, China University of Petroleum, China
- Zhen Wang, Hangzhou Dianzi University, China\
- Qun Jin, Waseda University, Japan
- Vincenzo Piuri, University of Milan, Italy
Submissions for this issue will close on December 1, 2022
Download the Call for Special Issue (PDF).
Special Issue on Social Studies, Human Factors and Applications in Metaverse
The emergence of the blockchain-empowered metaverse will bring about a new online social relationship. For example, decentralized autonomous organizations (DAOs) promise to provide users with an emerging social and entertainment relationship in the metaverse. Social computing predicts the operation law and future development trend of the metaverse by studying user behavior and social relationships. In addition, it is easier to collect the data on the blockchain and make a detailed evaluation to better support the society of the metaverse. The unprecedented focus on and investment in the metaverse will speed up the development and breakthrough of related technologies, which will produce a series of open research questions about every aspect of the metaverse, including blockchain infrastructure and the ecosystem. Therefore, this special issue aims to offer a platform for researchers from both academia and industry to publish recent research findings and to discuss opportunities, challenges, and solutions related to the metaverse. This special issue solicits original research papers about state-of-the-art approaches, methodologies, insights, and technologies enabling efficiency, and theories and practical applications towards the realization of the metaverse. Potential topics of interest include but are not limited to the following:
- Quantitative and qualitative analysis for the metaverse social ecosystem
- Social behaviors/network modeling for the metaverse ecosystem
- Quality of Experience (QoE) studies in metaverse
- Visualization for big data in metaverse social ecosystem
- Visualization tools and implementation in metaverse
- Novel social applications and services in the metaverse
- Novel DAOs design including incentive mechanism and governance for the metaverse
- Novel Decentralized Finance (DeFi) support for the metaverse
- Novel social network applications for metaverse
- Novel ubiquitous access techniques for the metaverse
- Novel methods to solve the network challenges and issues for the metaverse
- Other social research topics that are closely related to metaverse systems
Guest Editors:
- Wei Cai, The Chinese University of Hong Kong, Shenzhen, China
- Jian Zhao, University of Waterloo, Canada
- Xinning Gui, The Pennsylvania State University, USA
- Mounira Msahli, Telecom Paris, France
- Victor C.M. Leung, Shenzhen University / The University of British Columbia, China / Canada
Submissions for this issue will close on May 31, 2022
Download the Call for Special Issue (PDF).
Special Issue on Federated Learning-Based Computing for Socially Implemented IoMT Systems: How Will Healthcare Systems Change?
The current advances of wearable sensors show the shining future of socially implemented internet of medical things (IoMT) devices (e.g., smartwatches). However, machine learning approaches in these devices cannot be applied well, because almost all the processing in the IoMT devices is now being performed in classic forms (centralized computing) or based on cloud services. This special issue will try to extend our knowledge about how to apply collaborative learning to IoMT considering social edge/fog nodes’ facilities.
Guest Editors:
- Dr. Chinmay Chakraborty, Birla Institute of Technology, Mesra, India
- Dr. Mohammad Khosravi, Persian Gulf University, Iran
- Dr. Alireza Jolfaei, Macquarie University, Australia
- Dr. Gwanggil Jeon, Incheon National University
- Dr. Joel J. P. C. Rodrigues, SENAC Faculty of Ceará, Fortaleza – CE, Brazil
- Dr. Mohammad Khosravi, Persian Gulf University, Iran
- Dr. Marco Anisetti, University of Milan, Italy
- Dr. Seunggil Jeon, Samsung Electronics, South Korea
- Dr. Gabriella Casalino University of Bari, Italy
Submissions for this issue will close on June 30, 2022
Download the Call for Special Issue (PDF).
Special Issue on Social Computing and Societies 5.0: Toward Social Intelligence via Cyber Movement Organizations
This special issue aims to explore a wide range of issues related to social computing and societies 5.0, including the key technologies in social computing, and the potential issues and situations in the future intelligent society.
Guest Editors:
- Associate Prof. Xiao Wang, Institute of Automation, Chinese Academy of Sciences, China (Corresponding Editor)
- Prof. Sunshine Zhang, New York University, United States 3)
- Prof. Zhe Wan, Beijing Normal University, China 4)
- Prof. Jiade Luo, Tsinghua University, China 5)
- Prof. Xiaofeng Meng, Renmin University, China 6)
- Prof. Fei-Yue Wang, Institute of Automation, Chinese Academy of Sciences, China
Submissions for this issue will close on February 1, 2022
Download Call for Special Issue (PDF).
Special Issue on Knowledge-Infused Learning for Computational Social Systems
Over the last decades, research on computational social systems has gained much more attention, with thousands of researchers and practitioners leveraging diverse research findings and experimental models to enrich this domain. Thanks to the digital age, which has made the computational social system a reality. However, the integration of this technology in our daily lives leads to the generation of enormous amounts of data. The scale of this data is vast, and it presents unprecedented opportunities to examine complex social behaviours, ranging from the proliferation of infectious disease to socio-economic disparity. Probably these instances were further enhanced with the associated research findings.
Guest Editors:
- Tu Nguyen (Lead Guest Editors), Kennesaw State University, USA.
- Vincenzo Piuri, University of Milan, Italy
- Joel Rodrigues , Federal University of Piauí (UFPI), Teresina – PI, Brazil
- Lianyong Qi, Qufu Normal University, China
- Shahid Mumtaz, Instituto de Telecomunicações, Portugal
- Warren Huang-Chen Lee, National Chung Cheng University, Taiwan
Submissions for this issue will close on October 5, 2022
Download Call for Special Issue (PDF).
Special Issue on Advanced Cognitive Computing for Data-Driven Computational Social Systems
This special issue aims to solicit high-quality original research papers, which address the cutting-edge theories, models, and applications for data-driven computational social systems, supported by advanced cognitive computing technologies.
Guest Editors:
- Wei Wang, Sun Yat-sen University, China
- Vincenzo Piuri, University of Milan, Italy
- Takuro Sato, Waseda University, Japan
- Moayad Aloqaily, xAnalytics Inc., Canada
- Keping Yu, Waseda University, Japan
Submissions for this issue will close on December 31, 2021
Download Call for Special Issue (PDF).
Special Issue on Behavioral Modeling, Learning, and Adaptation in Cyber-physical Social Intelligence
Technological innovations have led to the emergence of digital finance such as online payment, online insurance, online lending, and supply chain finance. Digital finance has greatly facilitated people’s lives, accelerated the circulation of capital in various fields, and enhanced the vitality of financial markets. However, it exposes many increasing risks and hidden dangers such as stock volatility, trading fraud, and privacy leakage. In addition, the storage security and highperformance computing of financial big data also faces challenges. How to calculate, control, manage, and utilize effectively financial big data in order to ensure financial security, especially with the help of artificial intelligence technology, is an important research field. The special issue aims to explore a wide range of issues related to financial security. The central theme of the special issue is Big Data and Computational Social Intelligence for Guaranteed Financial Security, paying close attention to artificial intelligence, digital currency, blockchain, fraud detection and control, secure storage and high-performance computing technologies, as well as other studies and applications closely related to financial security. Topics to be covered include, but are not limited to, the following:
- Data mining and knowledge automation for financial security
- Financial risk assessment and forecasting such as stock forecasting and online lending
- Privacy protection technology for financial security
- Threat models and attack technique to finance
- Blockchain and digital currency
- Legal, ethical and societal aspects of digital currency
- Regulatory technologies and policies for digital finance
- Storage security and high-performance computing of financial big data
- Prevention of financial crimes such as transaction fraud, money laundering, illegal financing, and tax evasion
Important Dates
- Submissions for this issue will close on May 31, 2022
Guest Editors:
- Ying (Gina) Tang, Rowan University, USA
- Jiacun Wang, Monmouth University, USA
- Hui Yu, University of Portsmouth, UK
- Amir Hussain, Edinburgh Napier University, UK
- Giancarlo Fortino, University of Calabria, Italy
- Fei-Yue Wang, Chinese Academy of Sciences, China
Submissions for this issue will close on May 31, 2022
Download Call for Special Issue (PDF).
Special Issue on Generating Human Readable Explanations in NLP
The aim of this Special Issue is to attract explainable methods to generate human readable explanations with the purpose to stimulate discussion on the design, use and evaluation of novel Explainable Deep Learning models as the critical knowledge-discovery drivers to recognize, interpret, process and simulate human emotion for various NLP tasks.
Guest Editors:
- Imran Razzak, Deakin University, Australia (Corresponding Editor)
- Reda Bouadjenek, Deakin University, Australia
- Aamir Cheema, Monash University, Australia
- Ibrahim A Hameed, NTNU, Norway
- Guandong Xu, University of Technology, Sydney, Australia
- Amin Beheshti, Macquarie University, Australia
Submissions for this issue will close on December 26, 2021
Download Call for Special Issue (PDF).
Special Issue on Computational Social Systems for COVID-19 Emergency Management and Beyonds
This special issue aims to provide a much urgent and needed research work report in response to the ongoing COVID-19 pandemic, and share novel ideas, techniques and results on computational social systems based smart emergency.
Guest Editors:
- Jun Jason Zhang, Wuhan University (Corresponding Editor)
- Fei-Yue Wang, The State Key Laboratory for Management and Control of Complex Systems
- Yong Yuan, Institute of Automation, Chinese Academy of Sciences
- Guandong Xu, University of Technology Sydney
- Huan Liu, Arizona State University
- Wei Gao, Singapore Management University
- Shoaib Jameel, University of Essex
- Imran Razzak, Deakin University
- Peter Eklund, Deakin University
- Sheraz Ahmed, German Research Center for Artificial Intelligence
- Rui Qin, Institute of Automation, Chinese Academy of Sciences
- Juanjuan Li, Beijing Institute of Technology
- Xiao Wang, Qingdao Academy of Intelligent Industries
- De-Nian Yang, Academia Sinica, Taiwaz
- Damla Turgut, University of Central Florida, USA
- Abderrahim Benslimane, University of Avignon, France
- Neeli Prasad, SmartAvatar B.V., Netherlands
- Kwang-Cheng Chen, University of South Florida, USA
Submissions for this issue will close on June 30, 2020
Download Call for Special Issue (PDF).
Special Issue on Collaborative Edge Computing for Social Internet of Things Systems
This special issue intends to solicit original research and practical contributions from both industry and academia to advance collaborative edge computing in social IoT systems, regarding the corresponding architecture, technologies and applications.
Guest Editors:
- Zhaolong Ning, Dalian University of Technology, China
- MengChu Zhou, New Jersey Institute of Technology, USA
- Yong Yuan, Institute of Automation, Chinese Academy of Sciences, China
- Edith C. H. Ngai, Uppsala University, Sweden
- Ricky Y. K. Kwok, The University of Hong Kong, Hong Kong
Download Call for Special Issue (PDF).
Special Issue on Hybrid Human-Artificial Intelligence for Social Computing
This special issue aims to bring together researchers from both industry and academia to explore the potential of H-AI for social computing, including novel theories, concepts and paradigms as well as key techniques and typical applications.
Guest Editors:
- Weishan Zhang, China University of Petroleum (East China), China
- Huansheng Ning, University of Science and Technology Beijing, China
- Lu Liu, University of Leicester, UK
- Qun Jin, Waseda University, Japan
- Vincenzo Piuri, University of Milan, Italy
Submissions for this issue will close on October 30, 2019
Download Call for Papers (PDF).
Special Issue on Social Sensing and Privacy Computing in Intelligent Social Systems
This special issue is devoted to the most recent developments and research outcomes addressing the related theoretical and practical aspects on social sensing and privacy computing in intelligent social systems, and it also aims to provide worldwide researchers and practitioners an ideal platform to innovate new solutions targeting at the corresponding key challenges.
Guest Editors:
- Yulei Wu, University of Exeter, United Kingdom
- Fei Hao, Shaanxi Normal University, Xi’an, China
- Juanjuan Li, Qingdao Academy of Intelligent Industries, China
- Neil Y. Yen, The University of Aizu, Japan
- Yi Pan, Georgia State University, USA
- Victor C.M. Leung, University of British Columbia, Canada
Submissions for this issue will close on June 30, 2019.
Download Call for Papers (PDF).
Special issue on Advanced Machine Learning on Cognitive Computing for Human Behavior Analysis
This special issue aims to provide a forum for researchers from the perspective of cognitive computing to present recent progress on state-of-the-art methods and applications to human behavior analysis.
Guest Editors:
- Yizhang JIANG. Jiangnan University, China.
- Liu Liu, Nanjing University of Posts and Telecommunications, China.
- Rui Qin, Institute of Automation,Chinese Academy of Sciences, Beijing, China.
- Jiacun Wang, Monmouth University, USA.
- Reza Zare, Department of Informatics, University of Leicester, UK.
Submissions for this issue will close on May 31, 2020.
Download Call for Papers (PDF).
Special Issue on Integrating Social Networks with IoT Solutions
Social networks are one of the most popular services in the last decade yet are still growing quickly. The Internet of Things (IoT) promises billions of smart devices interconnected that potentially will kickstart the next industrial revolution. Rapid advances in social networks, IoT, and other symbiotic technologies derive a strong need to integrate social networking into IoT and converge at a new paradigm named social Internet of Things (SIoT). The symbiosis of IoT and social networks integrates computing, communication, sensing and system engineering, which is to produce significant social implications for both the devices and humans.
Guest Editors:
- Prof. Jun Zhang, Department of Electrical and Computer Engineering, University of Denver, USA
- Dr. Shancang Li, Department of Computer Science, University of the West of England, UK
- Dr. Shuangshuang Han, The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, China
- Prof. Bill Buchanan, School of Computing, Edinburgh Napier University, UK
- Dr. Xiao Wang, Qingdao Academy of Intelligent Industries, China
- Dr. Theo Tryfonas, Faculty of Engineering, University of Bristol, UK
Submissions for this issue closed on February 28, 2018.
Download Call for Papers (PDF).
Special Issue on Parallel and Distributed Processing for Computational Social Systems
Computational methods to represent, model and analyze problems using social information have come a long way in the last decade. Computational methods, such as social network analysis, have provided exciting insights into how social information can be utilized to better understand social processes, and model the evolution of social systems over time. Meanwhile, the emergence of parallel architectures, in the form of multi-core/many-core processors, and distributed platforms, have provided new approaches for large-scale modeling and simulation, and new tools for analysis. This special issue provides a platform to bring together interdisciplinary researchers from areas, including computer science, applied mathematics, social sciences, and computer engineering, to showcase innovative research in computational social systems that leverage the emerging trends in parallel and distributed processing, computational modeling, and high performance computing.
Guest Editors:
- Dr. Eunice E. Santos, Illinois Institute of Technology, USA
- Dr. John Korah, Illinois Institute of Technology, USA
Submissions for this issue closed on January 31, 2018.
Download Call for Papers (PDF).
Special Issue on Augmenting Urban Brain with Visual and Social Intelligence
Cities are complex systems that comprise physical infrastructure, cyber information, and social communities. Urban brain is conceptualized to shape the way a city runs in almost every aspect, from individuals’ daily lives to governments’ city management, such as urban planning and intelligent transportation systems. Visual intelligence combines automatic analysis with interactive visualizations, and social intelligence manages complex social relations and environments. This special issue aims to bring together researchers from both visualization and social computing communities to push forward the R&D for urban brain by leveraging the most recent progress in visual and social intelligence.
Guest Editors:
- Prof. Wei Chen, State Key Lab of CAD&CG, Zhejiang University, China
- Prof. Yisheng Lv, The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences; Qingdao Academy of Intelligent Industries, China
- Prof. Andreas Kerren, Department of Computer Science, Linnaeus University, Sweden
- Dr. Jing Xia, Ali-cloud, Alibaba, China
- Dr. Wei Zeng, Future Cities Laboratory, ETH Zurich, Switzerland
Submissions for this issue closed on May 31, 2018.
Download Call for Papers (PDF).
Special Issue on Blockchain-based Secure and Trusted Computing for IoT
Both the IoT and blockchain are two of the most transformative technologies in the world today. By employing the blockchain, IoT solutions can enable secure, trusted messaging between devices and maintain a decentralized, trusted leger of all transactions without the need to of centralized authority and management. This special issue aims to bring together researchers from both academia and industry to discuss the most recent advances on integrating social network with IoT solutions.
Guest Editors:
- Dr. Shancang Li, Department of Computer Science, University of the West of England, UK
- Dr. Yong Yuan, Institute of Automation, Chinese Academy of Sciences, China
- Prof. Jun Zhang, Department of Electrical and Computer Engineering, University of Denver, USA
- Prof. Bill Buchanan, School of computing, Edinburgh Napier University, UK
- Prof. Erwu Liu, School of Electronics Information Engineering, Tongji University, China
- Dr. Ramesh Ramadoss, IEEE P2418 Blockchain WG Chair & IEEE Blockchain Initiative Co-Chair, USA
Submissions for this issue will close on May 31, 2018 – Deadline Extended to December 31, 2018.
Download Call for Papers (PDF).
Special Issue on Human-Centric Cyber Social Computing
This special issue aims to seek new understanding of attributes common to human and cyber society, and reveal theoretical and practical problems of cyber social systems in a computational way. We solicit high-quality academic and technical papers addressing issues, challenges and promising solutions extensively related to human-centric cyber social computing.
Guest Editors:
- Qun Jin, Waseda University, Japan
- Weimin Li (Corresponding Editor), Shanghai University, China
- Song Guo, The Hong Kong Polytechnic University, Hong Kong, China
- Sethuraman Panchanathan, Arizona State University, USA
Submissions for this issue will close on Dec. 1, 2018 – Deadline Extended to February 1, 2019.
Download Call for Papers (PDF).
Special Issue on Computational Social Science for Public Policy and Citizen Wellbeing
This special issue is interested in papers that demonstrate how computational methods are used to solve social science problems related to public policy and citizen wellbeing. In other words, the special issue seeks social science studies using computational methods.
Guest Editors:
- Jonathan Zhu, City University of Hong Kong, China
- Xiaofeng Meng, Renmin University of China, China
- Xiaoming Li, Peking University, China
Submissions for this issue will close on June 30, 2018 – Deadline Extended to August 31, 2018.
Download Call for Papers (PDF).
Special Issue on Advances of Social Media Analytics for Behavioural Healthcare Systems: Theory, Methods and Applications
The central theme of this special issue is on the development and application of advanced Social Media Analytics for behavioural healthcare systems, where current theories, approaches, applications to leverage technology to promote behaviour health, including social influence analysis, social networks analytic, security, trust and privacy of social data, and large-scale medial data analytics for behaviour healthcare applications are the focus areas, and broad aspects and issues will be well discussed.
Guest Editors:
- Dr. Po Yang, Liverpool John Moores University, UK
- Prof. Bin Sheng, Shanghai Jiao Tong University, China
- Prof. Wenyan Wu, Birmingham City University, UK
- Dr. Yong Yuan, Institute of Automation, Chinese Academy of Sciences, China
Submissions for this issue will close on August 31, 2018 – Deadline Extended to November 30, 2018.
Download Call for Papers (PDF).
Special Issue on Ransomware and Its Social Impacts
This Special Issue will focus on the need to create formal methods and models to address ransomware and its threat to critical infrastructure. Ransomware is the malicious software that locks a computer until an extorted fee or ransom is paid for the key to unlock it. This ransom is usually paid in a “virtual currency” over the Internet, but it may also be paid in actual currency. Extortionists are becoming more sophisticated in their attacks, and their successful attacks are creating disruptive effects on their victims’ systems. While many attacks have generally had an impact on individuals or a public or private entity, WannaCry and NotPetya were attacks on critical infrastructure that cascaded onto a broader population.
Guest Editors:
- (Main) Peter Chin, PhD, Boston University and Systems & Technology Research
- Daniel G. Wolf, Cyber Pack Ventures, Inc.
- Donald L. Goff, PhD, Cyber Pack Ventures, Inc.
- Angelos Keromytis, PhD, Defense Advanced Research Project Agency & Columbia University
- George Cybenko, PhD, Dartmouth College
- Rui Qin, PhD, Qingdao Academy of Intelligent Industries, China
Submissions for this issue will close on October 15, 2018