Abstract
Due to its convenience and low-cost, short message service (SMS) has been a very popular medium for communication for quite some time. Unfortunately, however, SMS messages are sometimes used in illicit acts, such as communication between drug dealers and buyers, extortion, fraud, scam, hoax, false reports of terrorist threats, and many more. This study is a forensic study on the authorship classification of SMS messages in the Likelihood Ration (LR) framework with the N-gram modelling technique. The aims of this study are to investigate 1) how accurately it is possible to classify the authors of SMS messages; 2) what degree of strength of evidence (LR) can be obtained from SMS messages and 3) how the classification performance and the LRs are affected by the sample size for modelling. The resultant LRs are calibrated by means of the logistic regress calibration technique. The results of the classification tests will be rigorously assessed from different angles, using the techniques proposed for automatic speaker recognition and forensic voice comparison.
| Original language | English |
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| Pages | 47-56 |
| Number of pages | 10 |
| Publication status | Published - 2011 |
| Event | 9th Australasian Language Technology Association Workshop, ALTA 2011 - Canberra, Australia Duration: 1 Dec 2011 → 2 Dec 2011 |
Conference
| Conference | 9th Australasian Language Technology Association Workshop, ALTA 2011 |
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| Country/Territory | Australia |
| City | Canberra |
| Period | 1/12/11 → 2/12/11 |