Toward Predicting Collective Behavior via Social Dimension Extraction

Authors:
Lei Tang;Huan Liu
Affiliations:
Arizona State University, Tempe;Arizona State University, Tempe
Venue:
IEEE Intelligent Systems
Year:
2010

Citing 0
Cited 6

A multi-resolution approach to learning with overlapping communities

Proceedings of the First Workshop on Social Media Analytics
Group Profiling for Understanding Social Structures

ACM Transactions on Intelligent Systems and Technology (TIST)
Simulating inter-organizational collaboration network: a multi-relational and event-based approach

Simulation
Understanding online groups through social media

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Identifying same wavelength groups from twitter: a sentiment based approach

ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
The learning system of collective behavior in students' social network

Computers and Electrical Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

The social-dimension-based learning framework (SocioDim) can help predict online behaviors of social media users given a network and the behavior information of some actors in the network.