The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Information network or social network?: the structure of the twitter follow graph
Abstract
In this paper, we provide a characterization of the topological features of the Twitter follow graph, analyzing properties such as degree distributions, connected components, shortest path lengths, clustering coefficients, and degree assortativity. For each of these properties, we compare and contrast with available data from other social networks. These analyses provide a set of authoritative statistics that the community can reference. In addition, we use these data to investigate an often-posed question: Is Twitter a social network or an information network? The "follow" relationship in Twitter is primarily about information consumption, yet many follows are built on social ties. Not surprisingly, we find that the Twitter follow graph exhibits structural characteristics of both an information network and a social network. Going beyond descriptive characterizations, we hypothesize that from an individual user's perspective, Twitter starts off more like an information network, but evolves to behave more like a social network. We provide preliminary evidence that may serve as a formal model of how a hybrid network like Twitter evolves.
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Cites
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The Anatomy of the Facebook Social Graph
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HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm
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Cited by
LINE: Large-scale Information Network Embedding
Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., & Mei, Q. (2015) · Proceedings of the 24th International Conference on World Wide Web · doi:10.1145/2736277.2741093 · Cited by 5,416
A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks
Antonakaki, D., Fragopoulou, P., & Ioannidis, S. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114006 · Cited by 265
Seabrook, E. M., Kern, M. L., Fulcher, B. D., & Rickard, N. S. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9267 · Cited by 144
A Digital Ethnography of Medical Students who Use Twitter for Professional Development
Chretien, K. C., Tuck, M. G., Simon, M., Singh, L. O., & Kind, T. (2015) · Journal of General Internal Medicine · doi:10.1007/s11606-015-3345-z · Cited by 84
The Effect of Recommendations on Network Structure
Su, J., Sharma, A., & Goel, S. (2016) · Proceedings of the 25th International Conference on World Wide Web · doi:10.1145/2872427.2883040 · Cited by 78
Self-citation
Metadata
- Authors
- Myers, S. A., Sharma, A., Gupta, P., & Lin, J.
- Venue
- Proceedings of the 23rd International Conference on World Wide Web
- Publisher
- ACM
- Published
- 2014-04-07
- Pages
- 493-498
- OpenAlex
- W2250844151
- Cited by
- 313
- References
- 15
- FWCI
- 26.39
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Myers, S. A., Sharma, A., Gupta, P., & Lin, J. (2014). Information network or social network?: the structure of the twitter follow graph. Proceedings of the 23rd International Conference on World Wide Web. https://doi.org/10.1145/2567948.2576939
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
