Bootstrapping Case study: Profiling internet offenders
<p>As part of his work, he has to profile internet offenders from their digital records. Basically, he gets data on suspect’s internet history. Each row is a website the suspect has visited. Each of these websites is flagged — either sexual or not. Based on this data, he has to profile if the suspect is an internet offender. Their hypothesis is that the more sexual content a suspect consumes, the more is their propensity to be an internet offender.</p>
<p>Ideally, if David has the entire internet history of a suspect (the population dataset), then he would use it to just calculate the percentage of sexual content in suspect’s web history. Then he could use a threshold to profile the suspect — as a hebephile, paedophile, coercive/violent and adult interests.</p>
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