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MX4023 Project: Random Graphs\
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Author: Marcell Veiner\t\
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Imagine organizing a party for guests who initially do not know each other, \
while offering them wine and cheese and you will soon see them chatting in \
groups of two to three. Now mention to Mary, one of your guests, that the red \
wine in the unlabeled dark green bottles is a rare vintage, much better than \
the other ones. If she shares this information only with her acquaintances, \
you may think that your expensive wine is safe, as she only had time to meet \
a few others so far. \
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Yet, you would be wrong. As the guests continue to mingle, subtle paths form \
between individuals that may still be strangers to each other. For example, \
while John has not yet met Mary, they have both met Mike, so there is an \
invisible path from John to Mary through Mike. As time goes on, the guests \
will be increasingly interwoven by such elusive links.\
\>", "Text",
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Random network theory tells us that we do not have to wait until all \
individuals get to know each other for our expensive wine to be in danger. \
Rather, soon after each person meets at least one other guest, an invisible \
network will emerge that will allow the information to reach all of them.\
\>", "Text",
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We tell Mary at the beginning of the party about the rare wine.\
\>", "Item",
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Each person at the party talks to 3 other for 30 minutes. This can be someone \
they have already met that night.\
\>", "Item",
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In mathematics, random graph is the general term to refer to a probability \
space over graphs, thus a random graph is described by a probability \
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perspective, random graphs are used to answer questions about the properties \
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Key ideas already appeared in sociology and biophysics [7; 8]\
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Mathematical foundation by Paul Erd\[ODoubleAcute]s and Alfr\[EAcute]d R\
\[EAcute]nyi \"On random Graphs\", published in 1959 [3] and then a \
seminal series of papers\
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Duncan J. Watts and Steven Strogatz bringing random graphs closer to \
real-world networks [9]\
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