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Extracting Social Events for Learning Better Information Diffusion Models
Published on Sep 27, 20136258 Views
Learning of the information diffusion model is a fundamental problem in the study of information diffusion in social networks. Existing approaches learn the diffusion models from events in social netw
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Chapter list
Extracting Social Events for Learning Better Information Diffusion Models00:00
Highlights00:18
Information diffusion model and events!00:55
Learning information diffusion model from events - 102:05
Learning information diffusion model from events - 202:28
Learning information diffusion model from events - 302:34
Learning information diffusion model from events - 403:11
Social Influence vs. External Influence03:47
Challenge 1: How do we define the sources of influence?04:40
Challenge 2: Inference dependency06:26
Definitions: data stream, event, and actions07:10
The Latent Action Diffusion Path (LADP) Model08:04
The LADP Model - 109:08
The LADP Model - 209:37
EM-based inference algorithm10:20
Experiment Setup10:52
Twitter semi-synthetic Dataset - 111:57
Twitter semi-synthetic Dataset - 212:04
Twitter semi-synthetic Dataset - 413:45
Twitter network14:11
DBLP Datasets14:56
Inferred socially-sourced portion15:10
Case study: two events in Twitter UIC community16:40
Conclusion17:11