The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
@spam: the underground on 140 characters or less
Abstract
In this work we present a characterization of spam on Twitter. We find that 8% of 25 million URLs posted to the site point to phishing, malware, and scams listed on popular blacklists. We analyze the accounts that send spam and find evidence that it originates from previously legitimate accounts that have been compromised and are now being puppeteered by spammers. Using clickthrough data, we analyze spammers' use of features unique to Twitter and the degree that they affect the success of spam. We find that Twitter is a highly successful platform for coercing users to visit spam pages, with a clickthrough rate of 0.13%, compared to much lower rates previously reported for email spam. We group spam URLs into campaigns and identify trends that uniquely distinguish phishing, malware, and spam, to gain an insight into the underlying techniques used to attract users.
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Cites
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
Measuring user influence in twitter: The million follower fallacy
Cha, M., Haddadi, H., Benevenuto, F., & Gummadi, K. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14033 · Cited by 3,022
A Bayesian Approach to Filtering Junk E-Mail
Sahami, M., Dumais, S., Heckerman, D. E., & Horvitz, E. (1998) · Cited by 1,206
Uncovering social spammers: social honeypots + machine learning
Lee, K., Caverlee, J., & Webb, S. (2010) · Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1835449.1835522 · Cited by 619
Spamming botnets: signatures and characteristics
Xie, Y., Yu, F., Achan, K., Panigrahy, R., Hulten, G., & Osipkov, I. (2008) · ACM SIGCOMM Computer Communication Review · doi:10.1145/1402946.1402979 · Cited by 339
Spamalytics: an empirical analysis of spam marketing conversion
Kanich, C., Kreibich, C., Levchenko, K., Enright, B., Voelker, G. M., Paxson, V., & Savage, S. (2008) · Proceedings of the 15th ACM conference on Computer and communications security · doi:10.1145/1455770.1455774 · Cited by 323
Self-citationStudying spamming botnets using Botlab
John, J. P., Moshchuk, A., Gribble, S. D., & Krishnamurthy, A. (2009) · Cited by 185
Spamscatter: characterizing internet scam hosting infrastructure
Anderson, D. S., Fleizach, C., Savage, S., & Voelker, G. M. (2007) · eScholarship (California Digital Library) · Cited by 179
Xie, Y., Yu, F., Achan, K., Panigrahy, R., Hulten, G., & Osipkov, I. (2008) · ACM SIGCOMM Conference (SIGCOMM) · doi:10.1145/1402958.1402979 · Cited by 123
The Koobface botnet and the rise of social malware
Thomas, K., & Nicol, D. M. (2010) · International Conference on Malicious and Unwanted Software · doi:10.1109/malware.2010.5665793 · Cited by 122
Self-citation
Cited by
Information credibility on twitter
Castillo, C., Mendoza, M., & Poblete, B. (2011) · Proceedings of the 20th international conference on World wide web · doi:10.1145/1963405.1963500 · Cited by 2,593
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
Gupta, A., Lamba, H., Kumaraguru, P., & Joshi, A. (2013) · Proceedings of the 22nd International Conference on World Wide Web Companion · doi:10.1145/2487788.2488033 · Cited by 573
Detecting and Tracking Political Abuse in Social Media
Ratkiewicz, J., Conover, M., Meiss, M., Goncalves, B., Flammini, A., & Menczer, F. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14127 · Cited by 579
Ratkiewicz (2011) · doi:10.1145/1963192.1963301 · Cited by 541
Metadata
- Authors
- Grier, C., Thomas, K., Paxson, V., & Zhang, M.
- Venue
- Proceedings of the 17th ACM conference on Computer and communications security
- Publisher
- ACM
- Published
- 2010-10-04
- Pages
- 27-37
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W2165701072
- Cited by
- 558
- References
- 13
- FWCI
- 34.41
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Grier, C., Thomas, K., Paxson, V., & Zhang, M. (2010). @spam: the underground on 140 characters or less. Proceedings of the 17th ACM conference on Computer and communications security. https://doi.org/10.1145/1866307.1866311
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
