NDLI: From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

Content Provider	IEEE Xplore Digital Library
Author	Linyun Yu Peng Cui Fei Wang Chaoming Song Shiqiang Yang
Copyright Year	2015
Abstract	Cascades are ubiquitous in various network environments. How to predict these cascades is highly nontrivial in several vital applications, such as viral marketing, epidemic prevention and traffic management. Most previous works mainly focus on predicting the final cascade sizes. As cascades are typical dynamic processes, it is always interesting and important to predict the cascade size at any time, or predict the time when a cascade will reach a certain size (e.g. an threshold for outbreak). In this paper, we unify all these tasks into a fundamental problem: cascading process prediction. That is, given the early stage of a cascade, how to predict its cumulative cascade size of any later time? For such a challenging problem, how to understand the micro mechanism that drives and generates the macro phenomena (i.e. cascading process) is essential. Here we introduce behavioral dynamics as the micro mechanism to describe the dynamic process of a node's neighbors getting infected by a cascade after this node getting infected (i.e. one-hop subcascades). Through data-driven analysis, we find out the common principles and patterns lying in behavioral dynamics and propose a novel Networked Weibull Regression model for behavioral dynamics modeling. After that we propose a novel method for predicting cascading processes by effectively aggregating behavioral dynamics, and present a scalable solution to approximate the cascading process with a theoretical guarantee. We extensively evaluate the proposed method on a large scale social network dataset. The results demonstrate that the proposed method can significantly outperform other state-of-the-art baselines in multiple tasks including cascade size prediction, outbreak time prediction and cascading process prediction.
Starting Page	559
Ending Page	568
File Size	380476
Page Count	10
File Format	PDF
ISSN	15504786
e-ISBN	9781467395045
DOI	10.1109/ICDM.2015.79
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Social network services Additives Analytical models Computational modeling Computer science Data models Dynamic Processes Prediction Information Cascades Social Network
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

Models of Communication Dynamics for Simulation of Information Diffusion

Uncovering and predicting the dynamic process of information cascades with survival model

Structure in online social networks: Bridging the micro-macro gap

A Generalized Linear Threshold Model for Multiple Cascades

Control and prediction of beliefs on social network

Topic Based Information Diffusion Prediction Model with External Trends

Modeling Information Propagation in Chinese Microblogs Based on User Activity Influence

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

Similar Documents

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics

Models of Communication Dynamics for Simulation of Information Diffusion

Uncovering and predicting the dynamic process of information cascades with survival model

Structure in online social networks: Bridging the micro-macro gap

A Generalized Linear Threshold Model for Multiple Cascades

Control and prediction of beliefs on social network

Topic Based Information Diffusion Prediction Model with External Trends

Modeling Information Propagation in Chinese Microblogs Based on User Activity Influence

From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics