Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 142 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 28 tok/s Pro
GPT-5 High 25 tok/s Pro
GPT-4o 59 tok/s Pro
Kimi K2 198 tok/s Pro
GPT OSS 120B 430 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Spreaders in the Network SIR Model: An Empirical Study (1208.4269v2)

Published 21 Aug 2012 in cs.SI and physics.soc-ph

Abstract: We use the susceptible-infected-recovered (SIR) model for disease spread over a network, and empirically study how well various centrality measures perform at identifying which nodes in a network will be the best spreaders of disease on 10 real-world networks. We find that the relative performance of degree, shell number and other centrality measures can be sensitive to B, the probability that an infected node will transmit the disease to a susceptible node. We also find that eigenvector centrality performs very well in general for values of B above the epidemic threshold.

Citations (13)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.