Call for Papers
WSDM 2014 Workshop: Diffusion Networks and Cascade
Analytics
Diffusion of various types of behavior, information, rumors, ideas and infectious
diseases are all instances of stochastic processes that occur over the edges of an
underlying network. A contagion appears at some node of a network and then spreads like
an epidemic from node to node over the edges of the network, creating a cascade. For
example, in case of information propagation, the contagion represents a piece of
information and infection events correspond to times when nodes mention or copy the
information from one of their neighbors in the network. Developing computational
methods to analyze different cascade patterns, understand the mechanism
underlying diffusion, and eventually predict the cascading outbreaks, is of paramount
importance since it would allow not only to stop disease spread, avoid rumor and
misinformation spread, or mitigate traffic congestion but also design optimal marketing
strategies, maximize sales of a product, or detect viral ideas and content in an early
stage.
Diffusion and cascades have been studied for many years in sociology, and different
theoretical models have been developed. However, experimental validation has been
always carried out in relatively small datasets. In recent years, with the
availability of large-scale network and cascade data, research on cascading and
diffusion phenomena has aroused considerable interests from various fields in computer
science. One of the main goals has been to discover different propagation patterns from
historical cascade data. In this context, understanding the mechanisms underlying
diffusion in both micro- and macro-scale levels and further develop predictive model
of diffusion are fundamental problems of crucial importance.
The main goal of this workshop is therefore to bring together researchers from academia
and industry as well as practitioners to share and discuss their different
perspectives, ideas and latest research problems on diffusion networks and cascade analytics.
Topics of Interest
Topics of interest for the workshop include (but are not limited to) the following:
- Cascade pattern mining and analysis
- Cascading behavior analysis and prediction
- Cascading outbreak detection and prediction
- Information diffusion in social networks
- Homophily, social contagion and causality
- Network inference from cascades
- Rumor, misinformation, and anti-spam detection
- Mobility patterns mining and analysis
- Disease dynamics and vaccination strategies in social networks
- Games in networks
- Link prediction in networks
Submission Guidelines
Papers must be formatted according to ACM guidelines
(http://www.acm.org/sigs/publications/proceedings-templates)
and style files to fit within 4 pages, including references, diagrams, and appendices if any. A
submitted paper must be self-contained and in English. PDF files must have all non-standard fonts embedded.
Papers should be submitted by email to cuip@tsinghua.edu.cn, with the title of
"DifNet Submission: + $the name of the first author$".
The review process will be single-blind. Therefore, please include the
author and affiliation information in the submission. Each submission
will be reviewed by at least three reviewers. Papers must report
original research not accepted or under submission to any
peer-reviewed journal or conference. Previous submissions in venues
with no formal proceedings or as posters are allowed, but must be indicated.
Key Dates
- Submission Deadline: December 1
- Acceptance Notifications: December 25
- Workshop: February 28
Workshop Organizers