SMS Spam Collection v.1
The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research. It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.

Composition

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: http://www.grumbletext.co.uk/.
  • 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: http://www.comp.nus.edu.sg/~rpnlpir/downloads/corpora/smsCorpus/.
  • A list of 450 SMS ham messages collected from Caroline Tag's PhD Thesis available at http://etheses.bham.ac.uk/253/1/Tagg09PhD.pdf.
  • 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: http://www.esp.uem.es/jmgomez/smsspamcorpus/. This corpus has been used in the following academic researches:

[1] Gómez Hidalgo, J.M., Cajigas Bringas, G., Puertas Sanz, E., Carrero García, 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., Gómez Hidalgo, J. M., and Puertas Sánz, 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., Gómez Hidalgo, J. M., and Puertas Sánz, 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.


Usage

The collection is composed by just one text file, where each line has the correct class followed by the raw message. We offer some examples bellow:

ham   What you doing?how are you?
ham   Ok lar... Joking wif u oni...
ham   dun say so early hor... U c already then say...
ham   MY NO. IN LUTON 0125698789 RING ME IF UR AROUND! H*
ham   Siva is in hostel aha:-.
ham   Cos i was out shopping wif darren jus now n i called him 2 ask wat present he wan lor. Then he started guessing who i was wif n he finally guessed darren lor.
spam  FreeMsg: Txt: CALL to No: 86888 & claim your reward of 3 hours talk time to use from your phone now! ubscribe6GBP/ mnth inc 3hrs 16 stop?txtStop
spam  Sunshine Quiz! Win a super Sony DVD recorder if you canname the capital of Australia? Text MQUIZ to 82277. B
spam  URGENT! Your Mobile No 07808726822 was awarded a L2,000 Bonus Caller Prize on 02/09/03! This is our 2nd attempt to contact YOU! Call 0871-872-9758 BOX95QU


Note: the messages are not chronologically sorted.
<<< Here you can download the SMS Spam Collection v.1 >>>

Please read carefully the included readme file.

We would appreciate:

  1. If you find this dataset useful, you make a reference to the paper below and the web page: http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/ in your papers, research, etc;
  2. Send us a message to tiago <AT> dt.fee.unicamp.br or jmgomezh <AT> yahoo.es in case you make use of the corpus.


Publication and More Information

We offer a comprehensive study of this corpus in the following paper. This work presents a number of statistics, studies and baseline results for several machine learning methods.

Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the Study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11), Mountain View, CA, USA, 2011. (preprint)


About

The SMS Spam Collection has been created by Tiago A. Almeida and José María Gómez Hidalgo.

We would like to thank Min-Yen Kan and his team for making the NUS SMS Corpus available.


(c) Tiago A. Almeida and José María Gómez Hidalgo, 2011.