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Katharina von Knop
1. http://www.ummah.com/forum,
2. http://talk.islamicnetwork.com
3. http://forum.ribaat.org,
4. http://minbar-sos.com/forum/.
Specifically, influential threads and activity involving authors identifiable by user
name constituted an important factor in this analysis.
Figure 1: Overall Forum Statistics 12 (Generated by the Dark Web Team)
Forum
# of
Authors
# of
Threads
# of
Messages
Average
Thread
Duration
(days)
Average
Messages
per
Thread
Forum Duration
Ummah 2,338 3,787 81,976 68 22 4/2002 - 2/2007
Islamicnetwork 885 3,761 30,469 77 8 6/9/2004 – 2//2007
Minbar-Sos 109 1,242 3,945 30 3 1/2006 – 1/2007
Ribaat 2,393 3,571 46,562 133 13 1/2002 – 1/2007
In order to analyze the content of these forums, the Dark Web Teams proposed the
following approach: Detection of “hot threads”, detection of “hot authors” and
analysis of the content for ideas.
“Hot Threads” were defined based on the thread score: the higher the thread score,
the “hotter” the thread. Based on this definition, the Dark Web Team developed the
following metric to calculate scores for every thread within a forum. This metric is
by no means being proposed as a perfect solution for detecting contagiousness, but
represents an initial exploration.
Thread Score = Fnorm(Np) X Fnorm (Vt) X Fnorm (Dt) X Fnorm (Nam) X
Fnorm (Nm)
- Np: the number of postings in a thread
- Vt: the volume of postings in a thread
- Dt: the duration of a thread
- Nam: the number of active members in a thread
- Nm: the number of members who have postings in a thread.
- Fnorm: normalize each variable to a range of [0,1].
In this case study, members who had more than one posting in a thread were
classified as active members. The thread metric to calculate scores for every author
within a forum was adapted. Analogous to the thread analysis, the higher the author
score, the “hotter” the author. This metric supplements the hot thread analysis.
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