<p>First of all, I'm not an expert in linguistic or study of languages. I think I understand what you're trying to do, and I don't know what's the best way to do it.</p>

<p>If I got it right, you want to determine some centrality measure for your words (that would explain the social network reference), to find those who are the most linked to others, is that it ?</p>

<p>The problem if you try that is that you will certainly find that the most central words are the most inintersting ones (the, if, then, some redundant adjectives...), if you don't apply a tokenization and lemmization procedure beforehand. Thus you could separate only nouns and stemming of verbs used, and then only you could try your approach. </p>

<p>Another problem that you must keep in mind is that words are important both by their presence and by their rarity (see tf-idf weight measure for instance).</p>

<p>To conclude, I did the following search on google :</p>

<p>"<em>n gram graph language centrality word</em>"</p>

<p>and found this paper that seems interesting for what you're asking (I might give it a look myself !) : </p>

<p><a href="http://arxiv.org/abs/1109.2128" rel="nofollow">LexRank: Graph-based Lexical Centrality as Salience in Text Summarization</a></p>
Network Analysis
<p>I have a problem for network. 
For one document I am extracting some information. I am drawing nice graphs for them. But in a document information flows. I am trying to depict it in graph like the way one reads a text flowing with text and then important most entity first and then the next important one.</p>

<p>To understand and grasp this problem what are the kinds of things I have to study or which aspect of network theory or graph theory deals with it.</p>

<p>If any one can kindly refer up.
Regs,
SK. </p>