BigSee
Co-occurrence Data and Social Network Analysis
There are several advantages of visualizing and analyzing co-occurrence data with tools from social network analysis. First, there has recently been an increasing effort to elaborate algorithms in network analysis more generally under the pressure to understand the operations of the Internet, but also of other networks in biological and physical systems (Da F. Costa et al., 2005). Social network analysts can profit from these developments which are theoretically informed by graph theory. Similarly, there has been an explosion of visualization techniques. Using PROXSCAL may be more appropriate for visualizing co-citation data than using Pajek, because PROXSCAL can take the measurement scale into account. However, Pajek allows the user to indicate the strength of the relation, as noted, in terms of the thickness of the lines. PROXSCAL and other MDS programs require users to draw the relevant lines and groupings themselves. In the above example, Figure 13 shows a mapping result similar to that of Figure 10 and Figure 11 because the data set under study is unique in that there are two distinctive sets of authors; reducing the co-citation matrix to a binary one did not affect the result significantly.
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Co-occurrence Data and Social Network Analysis
There are several advantages of visualizing and analyzing co-occurrence data with tools from social network analysis. First, there has recently been an increasing effort to elaborate algorithms in network analysis more generally under the pressure to understand the operations of the Internet, but also of other networks in biological and physical systems (Da F. Costa et al., 2005). Social network analysts can profit from these developments which are theoretically informed by graph theory. Similarly, there has been an explosion of visualization techniques. Using PROXSCAL may be more appropriate for visualizing co-citation data than using Pajek, because PROXSCAL can take the measurement scale into account. However, Pajek allows the user to indicate the strength of the relation, as noted, in terms of the thickness of the lines. PROXSCAL and other MDS programs require users to draw the relevant lines and groupings themselves. In the above example, Figure 13 shows a mapping result similar to that of Figure 10 and Figure 11 because the data set under study is unique in that there are two distinctive sets of authors; reducing the co-citation matrix to a binary one did not affect the result significantly.
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