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  • 5.1.4 Studying Four Major NetSci Researchers (ISI Data)

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5.1.4.5 Word Co-Occurrence Network
5.1.4.5 Word Co-Occurrence Network
5.1.4.5 Word Co-Occurrence Network

 

 

 

Note

The Extract Word Co-Occurrence Network algorithm has been updated. To run this workflow you will need to update the plugin by downloading the

 

 

 

In the Sci2 Tool, select "361 unique ISI Records" from the 'FourNetSciResearchers' dataset in the Data Manager. Run 'Preprocessing > Topical > Lowercase, Tokenize, Stem, and Stopword Text' using the following parameters:

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The largest speed increases from the database functionality can be found in the extraction of networks. First, compare the results of a co-authorship extraction with those from section 5.1.4 Studying Four Major NetSci Researchers (ISI Data)#5.1.4.2 Author Co-Occurrence (Co-Author) Network. Run 'Data Preparation > Database > ISI > Extract Co-Author Network' followed by 'Analysis > Networks > Network Analysis Toolkit (NAT)'. Notice that both networks have 247 nodes and 891 edges. Visualize the extracted co-author network in GUESS using 'Visualization > Networks > GUESS' and reformat the visualization using 'Layout > GEM' and 'Layout > Bin Pack.' To apply the default co-authorship theme, go to 'Script > Run Script' and find 'yoursci2directory/scripts/GUESS/co-author-nw_database.py'. The resulting network will look like Figure 5.21.

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