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A few people have emailed me to learn what responses were sent regarding my
query on transmission / attenuation (e.g., for disease, information flow,
It appears some early work (primarily by Linton Freeman et al) used
shortest-paths (geodesics) to estimate transmission, but this suffered from
some of the shortcomings of centrality measures (e.g., the shortest path is
not necessarily the most relevant one).
However, the development of Information Centrality appears to address that
by incorporating all paths, according to two responses. See
Stephenson-Zelen (1989) paper on information centrality and Noha Friedkin's
measures of centrality. For that matter, I think there's a presentation of
the algorithm for info centrality in Wasserman and Faust.
Of course, the algorithm will require more complex matrix algebra (e.g.,
matrix inversion) than shortest path measures, I believe.
I also found these articles on info centrality:
Social networks in Disease Transmission: the colorado springs study -
Rothenberg, Woodhouse, Potterat, Muth, Darrow and Klovdahl - NIDA research
Monograph #151 on social networks, drug abuse, and HIV transmission
And the following, which has a nice intro on various centrality algorithms:
Centrality measures and Information Flows in venture Capital Syndication
networks, by Mikko Jaaskelainen (2001).
I found both of those articles on a google search.
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