2013 ViralityPredictionandCommunityS

• (Weng et al., 2013) ⇒ Lilian Weng, Filippo Menczer, and Yong-Yeol Ahn. (2013). “Virality Prediction and Community Structure in Social Networks.” In: Scientific reports, 3.

Subject Headings: Virality Prediction Task.

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Virality+Prediction+and+Community+Structure+in+Social+Networks

Quotes

Abstract

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 ViralityPredictionandCommunityS	Lilian Weng Filippo Menczer Yong-Yeol Ahn			Virality Prediction and Community Structure in Social Networks