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 ( 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, 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