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Hoax exterminator


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Soin, J 2007 , 'Hoax exterminator', Honours thesis, University of Tasmania.

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This thesis evaluates the potential use of computational techniques to help
leverage community knowledge in order to stop hoax emails. Techniques
assessed include weighted term based document matching utilising Lp similarity
measures and a form of unweighted phrase based matching. These are tested for
their effectiveness regarding their ability to identify hoaxes, cope with the
evolution of hoaxes and the effects of user added content, and for their low false
positive rates. The overall system that these techniques are tested to be a part of
supports not only hoax identification, but also user education and feedback. It is
observed that the simpler techniques Care the best without generating a large
number of false positives, namely phrase based matching and document similarity
with an L 1 metric. L2 measurement is also shown to perform reasonably
effectively regarding this application, but suffers from over sensitivity when
highly similar hoaxes are compared. A detailed look is taken at hoax emails and
the reasons behind their propagation, and a concept system from which all that
has been described can be utilised has been outlined. The effectiveness of some
of the techniques trialed coupled with a good understanding of both hoax emails
and the benefits and limitations that exist when utilising this community content
indicate that this fusing of community and technology has great potential.

Item Type: Thesis - Honours
Authors/Creators:Soin, J
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