[CS4423]: Add Lecture 02 notes & materials
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% \newcommand{\secref}[1]{\textbf{§~\nameref{#1}}}
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% \newcommand{\secref}[1]{\textbf{§~\nameref{#1}}}
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\newcommand{\secref}[1]{\textbf{§\ref{#1}~\nameref{#1}}}
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\newcommand{\secref}[1]{\textbf{§\ref{#1}~\nameref{#1}}}
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\usepackage[most]{tcolorbox}
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\usepackage{changepage} % adjust margins on the fly
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\usepackage{changepage} % adjust margins on the fly
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\usepackage{amsmath,amssymb}
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\usepackage{amsmath,amssymb}
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@ -203,5 +204,69 @@ Another interesting network concept is the \textbf{small-world effect}, which is
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Here, \textbf{distance} is usually measured by the number of edges one would need to cross over when travelling along a \textbf{path} from one vertex to another.
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Here, \textbf{distance} is usually measured by the number of edges one would need to cross over when travelling along a \textbf{path} from one vertex to another.
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In real-world social networks, the distance between people tends to be rather small.
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In real-world social networks, the distance between people tends to be rather small.
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\section{Graphs}
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A \textbf{graph} can serve as a mathematical model of a network.
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Later, we will use the \mintinline{python}{networkx} package to work with examples of graphs \& networks.
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\subsection{Example: The Internet (circa 1970)}
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\begin{figure}[H]
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\centering
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\includegraphics[width=0.7\textwidth]{./images/f7dec1970.jpg}
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\caption{
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The Internet (more precisely, ARPANET) in December 1970.
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Nodes are computers, connected by a link if they can directly communicate with each other.
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At the time, only 13 computers participated in that network.
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}
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\end{figure}
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\begin{code}
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\begin{minted}[linenos, breaklines, frame=single]{text}
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UCSB SRI UCLA
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SRI UCLA STAN UTAH
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UCLA STAN RAND
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UTAH SDC MIT
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RAND SDC BBN
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MIT BBN LINC
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BBN HARV
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LINC CASE
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HARV CARN
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CASE CARN
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\end{minted}
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\caption{\texttt{arpa.adj}}
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\end{code}
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The following \textbf{diagram}, built from the adjacencies in \verb|arpa.adj|, contains the same information as in the above figure, without the distracting details of US geography;
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this is actually an important point, as networks only reflect the \textbf{topology} of the object being studied.
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\begin{code}
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\begin{minted}[linenos, breaklines, frame=single]{python}
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H = nx.read_adjlist("../data/arpa.adj")
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opts = { "with_labels": True, "node_color": 'y' }
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nx.draw(H, **opts)
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\end{minted}
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\caption{\texttt{arpa.adj}}
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\end{code}
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\begin{figure}[H]
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\centering
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\includegraphics[width=0.7\textwidth]{./images/qwe_download.png}
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\caption{ The ARPA Network as a Graph }
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\end{figure}
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\subsection{Simple Graphs}
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A \textbf{simple graph} is a pair $G = (X,E)$ consisting of a finite set $X$ of objects called \textit{nodes}, \textit{vertices}, or \textit{points} and a set of \textit{links} or \textit{edges} $E$ which are each a set of two different vertices.
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\begin{itemize}
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\item We can also write $E \subseteq \binom{X}{2}$, where $\binom{X}{2}$ ($X$ \textit{choose} 2) is the set of all $2$-element subsets of $X$.
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\item The \textbf{order} of the graph $G$ is denoted as $n = |X|$, where $n$ is the number of vertices in the graph.
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\item The \textbf{size} of the graph is denoted as $m = |E|$, where $m$ is the number of edges in the graph.
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Naturally, $m \leq \binom{n}{2}$.
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\end{itemize}
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\subsubsection{Example}
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$G=(X,E)$ with $X = \{ A, B, C, D \}$ and $E = \{ \{AB\}, \{BC\}, \{BD\}, \{CD\} \}$, so $G$ is a graph of order $4$ and size $4$.
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We can be lazy and write $\{ A, B \}$ as just $AB$, so $E = \{ AB, BC, BD, CD \}$.
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\end{document}
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\end{document}
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year4/semester2/CS4423: Networks/notes/images/f7dec1970.jpg
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year4/semester2/CS4423: Networks/notes/images/qwe_download.png
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year4/semester2/CS4423: Networks/slides/CS4423-W01-2.html
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year4/semester2/CS4423: Networks/slides/CS4423-W01-2.html
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