Automated Spam Detection in Short Text Messages

  • Gaurav GoswamiEmail author
  • Richa Singh
  • Mayank Vatsa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 390)


Increase in the popularity and reach of short text messages has led to their usage in propagating unsolicited advertising, promotional offers, and other unwarranted material to users. This has led to a high influx of such spam messages. In order to protect the interests of the user, several countermeasures have been deployed by telecommunication companies to hinder the volume of such spam. However, some volume of spam messages still manage to avoid these measures and cause varying degree of annoyance to users. In this chapter, an automated spam detection algorithm is proposed to deal with the particular problem of short text message spam. The proposed algorithm performs the two class (spam, ham) classification using stylistic and text features specific to short text messages. The algorithm is evaluated on three databases belonging to diverse demographic settings. Experimental results indicate that the proposed algorithm is highly accurate in detecting spam in short messages and can be utilized by a wide variety of users to reduce the volume of spam messages.


Text Feature Text Message Short Message Service Word Count Short Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the authors of [17] for providing the SMS dataset.


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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Indraprastha Institute of Information TechnologyDelhiIndia

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