[CFP] #TheWebConf 2023 - Social Network Analysis and Graph Algorithms Track

[hady...@gmail.com]

We invite research contributions to the Social Network Analysis and Graph Algorithms Track at the 32nd edition of #TheWebConf 2023, to be hosted at Austin, TX, US, on April 30 - May 4, 2023.

Abstract: October 6, 2022
Full paper: October 13, 2022
Rebuttal: December 15 - 22, 2022
Notification: January 25, 2023

Link: https://www2023.thewebconf.org/calls/research-tracks/social-graph/

Social network platforms have enabled new forms of digital communication by connecting people via rich interactions with digital objects, diverse sources of information, and various services. Users on social media are concurrently consumers and producers of digital content, which continue to evolve their behaviors on these platforms from static to increasingly interactive content sharing. The massive volume of resulting data has created an unprecedented opportunity to address structural and behavioral questions to discover these new forms of communications and social digital behaviors. Studying these new types of interactions and data is an unprecedented opportunity to address both new and longstanding questions across and between a number of different fields of research, such as computer science, social science, graph theory, behavioral science, data science, and network science.

We encourage submissions that are relevant for the Web (for instance, as a technological infrastructure, or as a socio-economic system), in all areas of graph theory and algorithms, graph mining, and social network analysis, and, more broadly, work that integrates ideas from data mining, machine learning, social sciences, and computer science theory, as long as each submission addresses a Web-related scientific challenge explicitly stated in the submission.

Algorithms and Modeling:
* Algorithms for Web and Social Graph Representation, Reconstruction, Graph Identification, Subgraph and Motif Discovery
* Analysis of Heterogeneous, Signed, Attributed, and Annotated Networks
* Deep Learning for Web Graphs and Online Social Networks
* Succinct Data Structures for the Manipulation of Static and Dynamic Large Networks and Network-related Data
* Dynamic Network Analysis and Algorithms for Graph Streams
* Influence Propagation and Information Diffusion and Link Prediction
* Location-aware Social Network Analysis and Mobility
* Mining and Learning in Graphs with Missing Information and Noise
* Multi-relational Graph Analysis
* Network Representation Learning and Graph Embeddings
* Querying and Indexing Algorithms for Massive Graphs

Privacy and Security:
* Privacy-preserving Graph Algorithms
* Detecting, Understanding, and Combating Fake News (relevant to this track if the paper focus is a graph algorithm; please also read the CFP of the Security and Trust track and of the Web and Society track)
* Fairness, Bias, and Transparency of Graph Mining and Learning Algorithms (please also read the CFP of the Fairness, Accountability, Transparency, and Ethics of the Web track).
* Fraud, Spam, and Malice Detection on Graph Structure
* Cryptocurrency network mining and analysis

Social Media Applications:
* Social Media Analysis through the Lenses of Networks
* Social Mining and Social Search
* Social Recommendation Systems
* Behavioral Analysis of Online Communications

You can reach the track chairs Alessandra Sala, Emilio Ferrara, Yuxiao Dong at: sna-thewe...@easychair.org