Description

This corpus has been collected from free or free for research sources at the Internet: -> A collection of 425 SMS spam messages was manually extracted from the Grumbletext Web site. This is a UK forum in which cell phone users make public claims about SMS spam messages, most of them without reporting the very spam message received. The identification of the text of spam messages in the claims is a very hard and time-consuming task, and it involved carefully scanning hundreds of web pages. The Grumbletext Web site is: [Web Link]. -> A subset of 3,375 SMS randomly chosen ham messages of the NUS SMS Corpus (NSC), which is a dataset of about 10,000 legitimate messages collected for research at the Department of Computer Science at the National University of Singapore. The messages largely originate from Singaporeans and mostly from students attending the University. These messages were collected from volunteers who were made aware that their contributions were going to be made publicly available. The NUS SMS Corpus is avalaible at: [Web Link]. -> A list of 450 SMS ham messages collected from Caroline Tag's PhD Thesis available at [Web Link]. -> Finally, we have incorporated the SMS Spam Corpus v.0.1 Big. It has 1,002 SMS ham messages and 322 spam messages and it is public available at: [Web Link]. This corpus has been used in the following academic researches: [1] Gmez Hidalgo, J.M., Cajigas Bringas, G., Puertas Sanz, E., Carrero Garca, F. Content Based SMS Spam Filtering. Proceedings of the 2006 ACM Symposium on Document Engineering (ACM DOCENG'06), Amsterdam, The Netherlands, 10-13, 2006. [2] Cormack, G. V., Gmez Hidalgo, J. M., and Puertas Snz, E. Feature engineering for mobile (SMS) spam filtering. Proceedings of the 30th Annual international ACM Conference on Research and Development in information Retrieval (ACM SIGIR'07), New York, NY, 871-872, 2007. [3] Cormack, G. V., Gmez Hidalgo, J. M., and Puertas Snz, E. Spam filtering for short messages. Proceedings of the 16th ACM Conference on Information and Knowledge Management (ACM CIKM'07). Lisbon, Portugal, 313-320, 2007.