Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter
Abstract
There is a widespread intuitive sense that different kinds of information spread differently on-line, but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment. Here we study this issue on Twitter, analyzing the ways in which tokens known as hashtags spread on a network defined by the interactions among Twitter users. We find significant variation in the ways that widely-used hashtags on different topics spread.
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Inflammatory messages possess stronger viral potential in social networks.
“confirming that inflammatory messages possess stronger viral potential in social networks.”
From AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society (2025) · cites this paper as [87]
Standard information diffusion models cannot fully explain how inflammatory messages propagate because user sharing behaviors often deviate from typical patterns when encountering such content.
“Standard information diffusion models cannot fully explain how inflammatory messages propagate [87, 21], because user sharing behaviors often deviate from typical patterns when encountering such content.”
From AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society (2025) · cites this paper as [87]
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“Standard information diffusion models cannot fully explain how inflammatory messages propagate [84, 21], because user sharing behaviors often deviate from typical patterns when encountering such content.”
- Authors
- Romero, D. M., Meeder, B., & Kleinberg, J.
- Affiliations
- Cornell University (US)
- Carnegie Mellon University (US)
- Venue
- Proceedings of the 20th international conference on World wide web
- Publisher
- ACM
- Published
- 2011-03-28
- Pages
- 695-704
- OpenAlex
- W2145446394
- Cited by
- 1,082
- References
- 1
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 14 · 2023: 20 · 2022: 34 · 2021: 113 · 2020: 58 · 2019: 79 · 2018: 70 · 2017: 94 · 2016: 95 · 2015: 111 · 2014: 134 · 2013: 111 · 2012: 82
- FWCI
- 100.66
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International World Wide Web Conference (WWW) (publishedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- information dissemination, hashtags, Twitter, social networks, online information spread
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