  We propose a novel approach framed in terms of information theory and entropy
to tackle the issue of conspiracy theories propagation. We start with the
report of an event (such as 9/11 terroristic attack) represented as a series of
individual strings of information denoted respectively by two-state variable
Ei=+/-1, i=1,..., N. Assigning Ei value to all strings, the initial order
parameter and entropy are determined. Conspiracy theorists comment on the
report, focusing repeatedly on several strings Ek and changing their meaning
(from -1 to +1). The reading of the event is turned fuzzy with an increased
entropy value. Beyond some threshold value of entropy, chosen by simplicity to
its maximum value, meaning N/2 variables with Ei=1, doubt prevails in the
reading of the event and the chance is created that an alternative theory might
prevail. Therefore, the evolution of the associated entropy is a way to measure
the degree of penetration of a conspiracy theory. Our general framework relies
on online content made voluntarily available by crowds of people, in response
to some news or blog articles published by official news agencies. We apply
different aggregation levels (comment, person, discussion thread) and discuss
the associated patterns of entropy change.
