From visone user support
Word-Network Analysis (WNA) extracts a network from a text by interpreting the text as a chain of words and connecting relevant words within a certain interval.
Consider the following text example and take a closer look at the WNA procedure.
The two planes crashed into the towers of the World Trade Center in New York
First of all the WNA identifies the relevant words of the text. This preprocessing step includes:
- Filtering words with a length less than a preset word length
- Filtering stop words
- Filtering part of speech
The preprocessed text example could look like this:
plane crash tower world trade center new york
In the second and final step the network is constructed. Every word of the preprocessed text constitutes a node of the network, where equal words are represented by solely one node. The connections are created by using one of the following methods:
- Co-occurrence: Every word within in the same sentence is connected
- k-Windowing: Every word is connected to the k-1 subsequent words
The following figures show the final network depending on the utilized method.