SocialMeta 2024

The 3rd International Workshop on Social and Metaverse Computing, Sensing and Networking

(In conjunction with ACM SenSys'24)

Monday, November 4, 2024 / Hangzhou, China

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Keynote

Prof. Xiangjie Kong

Keynote: Data and Knowledge Driven Computational Urban Science
Abstract: The rapid development of online social networks, intelligent monitoring, automatic data collection, intelligent perception, and high-performance computing technologies in recent years has facilitated an explosive growth of big data. The accessibility of various data about humanity has greatly influenced the research topics or methods that researchers focus on. Using these data, traditional social issues can be examined from new perspectives, revealing more social phenomena. At the same time, the availability of data has led to the emergence of new research topics and methods. Consequently, exploring research themes in the field of data and knowledge driven computational social science has garnered increasing attention. Data and knowledge driven computational social science employs theories from network science along with data processing and analysis techniques from computer science to address these social issues, attracting significant interest from research institutions and scholars in fields such as computer science, network science, data science, management science, social science, behavioral science, and physics. This talk will illustrate some related research work in computational urban science based on urban big data in the field of smart cities.
Bio: Dr. Xiangjie Kong is currently a Full Professor and Vice Dean in the College of Computer Science & Technology, Zhejiang University of Technology (ZJUT), China. His research interests include big data, network science, and computational social science. 5 of his papers are selected as ESI- Hot Paper (Top 1‰), and 20 papers are ESI-Highly Cited Papers (Top 1%). His research has been reported by Nature Index and other medias. He has an h-index of 53 and i10-index of 130, and a total of more than 9500 citations to his work according to Google Scholar. He is named in the 2019 - 2024 world' s top 2% of Scientists List published by Stanford University, and the 2022-2024 Best Computer Science Scientists List published by Research.com. Dr. Kong received IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, IEEE CSCWD 2024 Best Paper Award, and The Natural Science Fund of Zhejiang Province for Distinguished Young Scholars.



Program

Monday, November 4, 2024

Venue: The Dragon Hotel Hangzhou, 120 Shuguang Road, Xihu Area, Hangzhou, China

8:30-8:40 Opening Session
8:40-9:40 Keynote

Data and Knowledge Driven Computational Urban Science

Prof. Xiangjie Kong (Zhejiang University of Technology)

9:40-10:25 Session 1
9:40-9:55
Influential-nodes Identification in Hypergraphs Based on Degree-heterogeneous Hierarchical Spherical Algorithm

Daxi Liu (Hangzhou Normal University), Susu Zhang (Hangzhou Normal University), Chuang Liu (Hangzhou Normal University), Xin Pei (Taiyuan University of Technology), Xiuxiu Zhan (Hangzhou Normal University)


9:55-10:10
Historical Patterns, Evolution of Models, and Future Perspectives of Interdisciplinary Collaboration an Empirical Study Based on Global Scientific Literature Data from 1950 to 2020

Hui Zou (Shanghai University), Kunpeng XU (Fudan University) , Liwei Chen (Fudan University), Boen Liu (Duke Kunshan University), Jingjing Qu (Shanghai Artificial Intelligence Laboratory), Xiaoming Fu (Fudan University)


10:10-10:25
Revealing the Difficulty in Jailbreak Defense on Language Models for Metaverse

Zuting Kang (The Hong Kong University of Science and Technology (Guangzhou)), Yule Liu (The Hong Kong University of Science and Technology (Guangzhou)), Zhen Sun (The Hong Kong University of Science and Technology (Guangzhou)), Jingyi Zheng (The Hong Kong University of Science and Technology (Guangzhou))

10:25-10:40 Group Photo and Tea Break
10:40-11:25 Session 2
10:40-10:55
A Novel Multi-view Hypergraph Adaptive Fusion Approach for Representation Learning

Zheng Yang (Shenyang University of Technology), Yang Yu (Shenyang University of Technology), Yue Zhang (Shenyang University of Technology), Shanshan Lin (Shenyang University of Technology)


10:55-11:10
EGGPU: Enabling Efficient Large-Scale Network Analysis with Consumer-Grade GPUs

Jiawei Tang (Fudan University), Min Gao (Fudan University), Yu Xiao (Aalto University), Cong Li (Fudan University), Yang Chen (Fudan University)


11:10-11:25
Fair Influence Maximization in Hypergraphs

Jinfeng Xie (Hangzhou Normal University), Su-Su Zhang (Hangzhou Normal University), Chuang Liu (Hangzhou Normal University), Xiu-Xiu Zhan (Hangzhou Normal University)


11:25-12:10 Session 3
11:25-11:40
AdSpectorX: A Multimodal Expert Spector for Covert Advertising Detection on Chinese Social Media

Zongmin Zhang (The Hong Kong University of Science and Technology (Guangzhou)), Yujie Han (Institut Polytechnique de Paris), Zhou Zhang (Dalian University of Technology), Yule Liu (The Hong Kong University of Science and Technology (Guangzhou)), Jingyi Zheng (Hong Kong University of Science and Technology (Guangzhou)), Zhen Sun (The Hong Kong University of Science and Technology (Guangzhou))


11:40-11:55
SCI-MKGC: A MKGC Method Based on Spatial Context and Interaction Attention

Rui Wen (Dalian Univerisity of Technology), Zhe Zhan (Dalian Univerisity of Technology), RuoLin Li (Dalian Univerisity of Technology), Duo Yu (Dalian Univerisity of Technology), Annie Chen (University of Wollongong), JiaXi Chen (Dalian Univerisity of Technology), Shuo Yu (Dalian Univerisity of Technology), Qiang Zhang (Dalian Univerisity of Technology)


11:55-12:10
Confronting The Dark Side of the Metaverse: A Vision of Criminal Punishment for Safeguarding Metaverse Users

Chan-In Sio (The Hong Kong Polytechnic Unversity), Xian Wang (The Hong Kong Polytechnic University), Lik-Hang Lee (The Hong Kong Polytechnic University)

12:10-12:15 Closing Remarks