A few chirps about twitter
Abstract
Web 2.0 has brought about several new applications that have enabled arbitrary subsets of users to communicate with each other on a social basis. Such communication increasingly happens not just on Facebook and MySpace but on several smaller network applications such as Twitter and Dodgeball. We present a detailed characterization of Twitter, an application that allows users to send short messages. We gathered three datasets (covering nearly 100,000 users) including constrained crawls of the Twitter network using two different methodologies, and a sampled collection from the publicly available timeline. We identify distinct classes of Twitter users and their behaviors, geographic growth patterns and current size of the network, and compare crawl results obtained under rate limiting constraints. Categories and Subject Descriptors C.4 [Performance of Systems]: [Measurement techniques, Modeling techniques]
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Although Twitter has been examined as a social microblog, as a social network, and as a messaging application, there are cultural affordances that are missed by each of these approaches.
“Although Twitter has been examined as a social microblog (Java et al., 2007), as a social network (Huberman, Romero, & Wu, 2008), and as a messaging application (Krishnamurthy, Gill, & Arlitt, 2008), there are cultural affordances that are missed by each of these approaches.”
From Distributed Blackness: African American Cybercultures (2020) · cites this paper as Krishnamurthy, Gill, & Arlitt, 2008
Cites
Measurement and analysis of online social networks
Mislove, A., Marcon, M., Gummadi, K. P., Druschel, P., & Bhattacharjee, B. (2007) · Proceedings of the 7th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1298306.1298311 · Cited by 3,057 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
What is Twitter, a social network or a news media?
Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652 · see citing works
Detecting spammers on social networks
Stringhini, G., Kruegel, C., & Vigna, G. (2010) · Proceedings of the 26th Annual Computer Security Applications Conference · doi:10.1145/1920261.1920263 · Cited by 791 · see citing works
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 · see citing works
Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg?
Chu, Z., Gianvecchio, S., Wang, H., & Jajodia, S. (2012) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2012.75 · Cited by 634 · see citing works
From the Blackhand Side: Twitter as a Cultural Conversation
Brock, A. (2012) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2012.732147 · Cited by 606 · see citing works
Brock, A. (2020) · doi:10.18574/9781479811908 · Cited by 235 · see citing works
Stringhini, G., Wang, G., Egele, M., Kruegel, C., Vigna, G., Zheng, H., & Zhao, B. Y. (2013) · Proceedings of the 2013 conference on Internet measurement conference · doi:10.1145/2504730.2504731 · Cited by 169 · see citing works
On the interpretation of digital trace data in communication and social computing research
Freelon, D. (2014) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2013.875018 · Cited by 132 · see citing works
“Everything is plentiful-except attention” attention data of scientific journals on social web tools
Kortelainen, T., & Katvala, M. (2012) · Journal of Informetrics · doi:10.1016/j.joi.2012.06.004 · Cited by 42 · see citing works
- Authors
- Krishnamurthy, B., Gill, P., & Arlitt, M.
- Affiliations
- AT&T (United States) (US)
- University of Calgary (CA)
- Venue
- Proceedings of the first workshop on Online social networks
- Publisher
- ACM
- Published
- 2008-08-18
- Pages
- 19-24
- OpenAlex
- W2000200507
- Cited by
- 697
- References
- 1
- Citations by year
- 2025: 5 · 2024: 9 · 2023: 3 · 2022: 8 · 2021: 25 · 2020: 20 · 2019: 15 · 2018: 33 · 2017: 26 · 2016: 54 · 2015: 56 · 2014: 69 · 2013: 85 · 2012: 73
- FWCI
- 81.07
- Type
- conference paper
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Computer Science › Information Systems › Web Data Mining and Analysis
- Physical Sciences › Computer Science › Information Systems › Web visibility and informetrics
- Keywords
- Twitter, social networks, Web 2.0, network characterization, user behavior, network size, rate limiting, crawling, short message service, user classification
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
