The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Competition among memes in a world with limited attention
Open accessAbstract
The wide adoption of social media has increased the competition among ideas for our finite attention. We employ a parsimonious agent-based model to study whether such a competition may affect the popularity of different memes, the diversity of information we are exposed to, and the fading of our collective interests for specific topics. Agents share messages on a social network but can only pay attention to a portion of the information they receive. In the emerging dynamics of information diffusion, a few memes go viral while most do not. The predictions of our model are consistent with empirical data from Twitter, a popular microblogging platform. Surprisingly, we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas.
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Cites
The origin of bursts and heavy tails in human dynamics
Barabási, A.-L. (2005) · Nature · doi:10.1038/nature03459 · Cited by 2,210
Everyone's an influencer: quantifying influence on twitter
Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011) · Proceedings of the fourth ACM international conference on Web search and data mining · doi:10.1145/1935826.1935845 · Cited by 1,689
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks
Aral, S., Muchnik, L., & Sundararajan, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908800106 · Cited by 1,207
Information contagion: an empirical study of the spread of news on digg and twitter social networks
Lerman, K., & Ghosh, R. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14021 · Cited by 813
Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number
Gonçalves, B., Perra, N., & Vespignani, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022656 · Cited by 638
Self-citation
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Beyond misinformation: Understanding and coping with the “post-truth” era.
Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2017.07.008 · Cited by 1,985
Twenge, J. M., Martin, G. N., & Spitzberg, B. H. (2019) · Psychology of Popular Media Culture · doi:10.1037/ppm0000203 · Cited by 703
Virality Prediction and Community Structure in Social Networks
Weng, L., Menczer, F., & Ahn, Y.-Y. (2013) · Scientific Reports · doi:10.1038/srep02522 · Cited by 512
Self-citationSocializing in emergencies—A review of the use of social media in emergency situations
Simon, T., Goldberg, A., & Adini, B. (2015) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2015.07.001 · Cited by 461
Hoaxy: A Platform for Tracking Online Misinformation
Shao, C., Ciampaglia, G. L., Flammini, A., & Menczer, F. (2016) · Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion · doi:10.1145/2872518.2890098 · Cited by 389
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Metadata
- Authors
- Weng, L., Flammini, A., Vespignani, A., & Menczer, F.
- Venue
- Scientific Reports
- Published
- 2012-03-29
- Volume
- 2
- Issue
- 1
- Pages
- 335-335
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2072606289
- Cited by
- 620
- References
- 5
- FWCI
- 37.22
- Type
- journal article
- Language
- en
- Open access
- gold
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