Workshop Program

The program of BSMDMA workshop is half-day with 2 keynote speeches and 3 paper presentations.

BSMDMA Workshop @ IJCAI 2019

Location: Sicily 2403, Venetian Macao Hotel Resort

Date: Sunday, August 11, 2019

08:50~09:00 Welcome
09:00~10:00 Opening Keynote
Graph Convolutional Neural Networks

Huawei Shen (Chinese Academy of Sciences, China)


10:00~10:15 [1] Semantic Graph Representation Learning in Attributed Networks
Meng Qin (Peking University) and Kai Lei (Peking University)

[Paper] [Slides]

10:15~10:30 Coffee Break
10:30~11:00 [2] RandomWalk Fundamental Tensor and Graph Importance Measures
Daniel Boley (University of Minnesota) and Alejandro Buendia (Microsoft)

[Paper] [Slides]

[3] Prediction of Information Cascades via Content and Structure Integrated Whole Graph Embedding
Xiaodong Feng (UESTC), Qihang Zhao (UESTC), and Zhen Liu (UESTC)

[Paper] [Slides]

11:00~12:00 Closing Keynote
The Dynamics, Uncertainty and Heterogeneity in Network Embedding

Xiangliang Zhang (KAUST, Saudi Arabia)


Keynote Speakers

Speaker: Prof. Huawei Shen

(Professor, Chinese Academy of Sciences, China)


Graph Convolutional Neural Networks


Convolutional neural networks (CNNs) have been successfully used in many machine learning problems, such as image classification and speech recognition, where there is an underlying Euclidean structure. One interesting research problem is how to generalize convolutional neural network to non-Euclidean data, for example, graph data. This talk will introduce the research progress on this direction, i.e., graph convolutional neural networks and their applications on some tasks, e.g., node classification, link prediction, graph classification.


Dr. Huawei Shen is a Professor at the Institute of Computing Technology, Chinese Academy of Sciences. He earned his Ph.D. degree from the University of Chinese Academy of Sciences in 2010. His research interests include social media analytics, web data mining, and deep learning on graph. He has published over 100 research papers in referred international journals, including PNAS, IEEE TKDE, Physical Review E, and conference proceedings, including WWW, SIGIR, AAAI, IJCAI, and CIKM. He regularly serves on the Program Committee for premier conferences like KDD, WWW, SIGIR, AAAI, IJCAI, CIKM, ICWSM etc.

Speaker: Prof. Xiangliang Zhang

(Associate Professor, KAUST, Saudi Arabia)


The Dynamics, Uncertainty and Heterogeneity in Network Embedding


Network embedding has been playing important roles in diverse network management and analysis applications. Social networks face challenges of the dynamics in network structure evolution, the uncertainty in social activities and the heterogeneity of node attributes. This talk will discuss the impact of these difficulties on network embedding, and introduce recent solutions to them based on variational autoencoder for encoding the uncertainty, Kalman Filter for learning the dynamic transition of node embeddings, and biased random walks for resolving the node heterogeneity. The obtained embedding results will be demonstrated in standard applications of node classification and link prediction, as well as dynamic user profiling and scholars’ research interest characterization.


Dr. Xiangliang Zhang is an Associate Professor of Computer Science and directs the Machine Intelligence and kNowledge Engineering (MINE) group at KAUST, Saudi Arabia. She earned her Ph.D. degree in computer science from INRIA-Universite Paris-Sud, France, in July 2010. She received M.S. and B.S. degrees from Xi’an Jiaotong University, China, in 2006 and 2003, respectively. Dr. Zhang's research mainly focuses on learning from complex and large-scale streaming and graph data. Dr. Zhang has published over 100 research papers in referred international journals and conference proceedings, including TKDE, SIGKDD, AAAI, IJCAI, ICDM, VLDB J, ICDE etc. She is the associated editor of Information Sciences and Health Information Science and Systems. She regularly serves on the Program Committee for premier conferences like SIGKDD, AAAI (Senior PC), IJCAI (Senior PC), ICDM, NIPS, ICML etc. Dr. Zhang is selected and invited to deliver an Early Career Spotlight talk at IJCAI-ECAI 2018.

Call for Papers

The rich proliferation of many social media platforms is widely by used people on smartphone devices all over the world. At the same time, the incremental data of online social networks (e.g., Facebook), microblogs (e.g., Twitter), multi-media sites (e.g., YouTube, Instagram) and user review sites (e.g., Yelp) are imposing new challenges for the efficient data management and analysis query processing. On one hand, online social networks are undergoing rapid changes, not only on the dynamic graph structure, but also in the new information of updating user profiles, new hashtags in posters, as well as breakthrough events. On the other hand, the size of social media data is becoming bigger and bigger due to, e.g., the explosion of new posters and also the massive amount of users. Utilizing new technologies for efficient handling big social media data management is of urgent importance. However, numerous essential issues in this area have yet to be explored, including data crawling and modeling, storage, indexes, querying and mining, privacy, and so on.

The 2019 International Workshop on Big Social Media Data Management and Analysis (BSMDMA2019) aims to provide a forum for presenting the most recent advances of online social media in data management and mining, related to web search and information retrieval, social network analysis, visualization and summarization, and network science. The BSMDMA2019 will be in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI'19) on August 10-16, 2019, Macao, China. We are particularly interested in articles that address how to handle query processing on large-scale and dynamic social media data as well as their novel applications for social media platforms. Topics of interest include but are not limited to:

  • Community Detection and Search
  • Network Embedding and Representation
  • Social Networks Crawling
  • Large-scale Complex Network Analysis
  • Big Graph Management and Mining
  • Keyword and Microblog Search
  • Text Summarization
  • Argumentation Mining
  • Privacy-aware Computing in Social Network
  • Social Content Processing
  • Role Identification and Relation Analysis in Social Network
  • Querying and Mining Problems on Location-based Social Networks
  • Evolution Patterns in Dynamics Graph Streaming
  • Distributed Graph Query Processing

Submission Guidelines

The submissions must be original (not previously published and not under review in other forums). We welcome the submission of regular research papers (up to 8 pages) as well as short papers (2-4 pages). The submission webpage for BSMDMA2019 is . Submissions should follow the regular IJCAI paper format and relates with our workshop topics. All papers will be peer reviewed, single-blinded. Accepted papers will be published as a collection of working papers, and presented either as a talk or a poster. Note that accepted papers by our workshop can be extended to submit to IJCAI and other premier conferences, which allows the submissions in no formally published proceedings (that is, as long as the published proceedings have no publisher and ISSN).


General Co-Chairs

  • William Kwok-Wai Cheung, Hong Kong Baptist University, Hong Kong
  • Kevin Chen-Chuan Chang, University of Illinois at Urbana-Champaign, USA

Program Co-Chairs

  • Di Jin, Tianjin University, China
  • Yunwen Lei, Southern University of Science and Technology, China
  • Jing Liu, Xidian University, China
  • Xin Huang, Hong Kong Baptist University, Hong Kong

​Program Committee

  • Yang Cao, Kyoto University, Japan
  • Bianfang Chai, Hebei Geological University, China
  • Wei-Lun Chang, Tamkang University, Taiwan
  • Bilian Chen, Xiamen University, China
  • Ming Chen, Hunan Normal University, China
  • Tommy Dang, Texas Tech University, USA
  • Yixiang Fang, The University of New South Wales, Australia
  • Yunlong Feng, State University of New York at Albany, USA
  • Francesco Gullo, UniCredit, Italy
  • Dongxiao He, Tianjin University, China
  • Hsiao-Wei Hu, Fu-Jen Catholic University, Taiwan
  • Yafei Li, Zhengzhou University, China
  • Dong Liu, Hunan Normal University, China
  • Qing Liu, Hong Kong Baptist University, Hong Kong
  • Zheng Liu, Nanjing University of Posts and Telecommunications, China
  • Caiyan Jia, Beijing Jiaotong University, China
  • Hangjin Jiang, ZheJiang University, China
  • Xiaoke Ma, Xidian University, China
  • Françoise Soulié, Tianjin University, China
  • Xiao Wang, Tsinghua University, China
  • Liang Wu, Southwestern University of Finance and Economics, China
  • Yubao Wu, Georgia State University, USA
  • Zhihao Wu, Beijing Jiaotong University, China
  • Changdong Wang, Sun Yat-sen University, China
  • Chuan Shi, Beijing University of Posts and Telecommunications, China
  • Yunya Song, Hong Kong Baptist University, Hong Kong
  • Liang Yang, Hebei University of Technology, China
  • Yu Yang, Simon Fraser University, Canada
  • Xiaofei Zhang, University of Memphis, USA
  • Zhongyuan Zhang, Central University of Finance and Economics, China
  • Xuehua Zhao, Shenzhen Institute & Information Technology, China
  • Fuzhen Zhuang, Chinese Academy of Sciences, China

Pervious Workshops

You can find more details of our previous workshops BSMDMA2017 and BSMDMA2018 .

Attending Conference

BSMDMA2019 is co-located with IJCAI2019, which will share information in attending the conference. Please check following important links before you plan your itinerary.

If you have any questions, please email: