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This is quite the persuasive selling of MultiNet. I have to admit I've found
many of its features very attractive and I love the look of many of the
graphs in the manual. I have a question, however, about its use for batch
processing. Does it have a useful mechanism for automating the same
operation (say correlating frequency of contact with an alter to alter's
vertex degree, or even simpler - the components in the egonet when ego is
not included) for a number of egonets, and exporting a table of results? I
couldn't find anything about this in the manual.
In general, this has always been my biggest sticking point with most
software 'applications' (UCInet, Pajek, NetMiner) as opposed to the more
versatile but difficult-to-learn software 'environments' such as R's SNA
package, GUESS and JUNG. Currently I'm using a mix of all the latter.
Nevertheless, I would prefer a simple point and click interface so long as I
don't have to click the same thing for every egonet.
..If that can't be done with MultiNet now, is that something you are looking
at for future releases?
Department of Sociology
University of Toronto
Microsoft Research (Volt)
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I received a message from Bill.Richards at approximately 12/19/05 9:55 PM.
Above is my reply.
> ***** To join INSNA, visit http://www.insna.org *****
> Hi Daniele,
> MultiNet started as an extended replacement for FATCAT, but it does so
> much more that there is little in common beyond the data model it uses.
> MultiNet's immediate ancestor was designed specifically to work with
> ego-centric data. MultiNet goes much further than its predecessor in
> that it is happy with continuous data as well as the categorical data
> that FATCAT wanted. It also does many more types of analysis than the
> earlier program, and it can use ordinary (non-ego-centric) data. Largely
> due to the mix of analytic techniques it incorporates, .MultiNet can
> extract information about patterns in the data that are otherwise not
> easily seen.
> MultiNet is an interactive menu-driven program for exploratory analysis
> and display of discrete and continuous multivariate network data. It has
> context-sensitive, interactive, on-line help, and always presents a
> color graphic representation of the data or the results of analysis. All
> graphics can be saved as bitmap or PostScript files. The program does
> ordinary univariate descriptive statistics, crosstabulation, analysis of
> variance, regression, and correlation. It also does network versions of
> crosstabulation, anova, correlation-regression in which it combines data
> that describes nodes with data that describes relationships between
> nodes into a single analytic model. It lets you mix node variables with
> link variables in a variety of kinds of analysis to explore the patterns
> in your network. While most network programs perform one or another type
> of structural analysis, MultiNet also does contextual analysis: it looks
> at attributes of people in the context of the relationships between and
> among them, and it looks at characteristics of relationships between
> people in the context of the attributes of the people. It is very happy
> with both ego-centric and ordinary whole-network data. It can easily
> deal with data that has many variables describing attributes of nodes
> and many that describe relationships between nodes.
> The program has a variety of flexible data manipulation capabilities. It
> can handle missing data. It performs continuous and discrete
> transformations, such as ordination, quantiles, recategorization. Sets
> of ranked variables can be inverted. It does linear, log, power, and z
> transforms. New variables can be created by transforming or combining
> existing ones in any manner describable by algebraic equations. The
> program also provides file viewing and editing capabilities. It can do
> four types of eigen decomposition of networks with up to 5,000 nodes for
> spectral analysis with interactive graphical display of results in 1, 2,
> or 3 dimensions, including link direction and/or strength, node
> attribute labels, and more options for graphic representation of eigen
> analysis results. The results of eigen analysis are integrated with the
> rest of the program so coordinates in eigen space can be used as
> variables in any other analysis the program does. Results of eigen
> decomposition can be used to create partitions that identify clusters or
> sets of structurally equivalent nodes. MultiNet does p* analysis on
> networks with up to 5,000 nodes, with interactive graphical display of
> results. Results of eigen analysis can be used to improve p* fits when
> using block structures. There is no easier way to do eigen analysis and
> p* modeling of networks. MultiNet made this picture:
> MultiNet wants two files of data: one is an ordinary rectangular
> cases-by-variables file describing the nodes. Use as many variables as
> you want and use hundreds of thousands of nodes if you have the data.
> Each node may be a person, an organization, an event, a publication, an
> author, a symptom, a dietary item, etc., etc. Some nodes may be people
> and others may be things that people have or do or attend.... The second
> file describes relations between pairs of nodes. It is organized as a
> rectangular dyads-by-variables file, in which each line of data
> describes the connections between a pair of nodes. (The data should only
> describe the connections that are present: if there is no connection
> between a specific pair of nodes, just don't say anything about that
> pair.) Use hundreds of variables if you wish -- each one describing a
> type of relationship or some characteristic of the interaction between
> the nodes that constitutes a relationship. These variables may be
> binary, scalar, or continuous. Links may be directed or undirected. The
> program can read data in csv files that most spreadsheet programs can
> An analysis may involve one or more variables from one of the files or
> variables from both files.
> The MultiNet page is at
> http://www.sfu.ca/~richards/Multinet/Pages/multinet.htm Among other
> things, this page includes information about how to obtain MultiNet.
> For a more complete description than the one above, go to the URL
> mentioned above and click on "MultiNet quick start"
> For the entire 309-page manual, go to the URL mentioned above and click
> on "MultiNet manual July, 2005"
> with my best wishes,
> Daniele Mascia wrote:
>> ***** To join INSNA, visit http://www.insna.org *****
>> Dear Socnetters,
>> we are conducing an analysis centered on the ego-networks of scientists
>> working in several international scientific institutions. Our idea is that of
>> investigating structural characteristics of the one-step neighborhood of the
>> surveyed scientists.
>> To date, we have found a few articles explaining concepts and charateristics
>> related to the ego-network, but we are still in search of materials about the
>> methodology to be used to deal with ego-network data. In particular, given a
>> set of ego-networks collected in spreadshit editors, we would like to know
>> which format is reccomended for importing such data in one of the available
>> software for network analysis (e.g. UCINET, Pajek...), and how to conduce
>> relative analyses.
>> Thanks in advance for any comments.
>> Best regards,
>> Daniele Mascia
>> Catholic University - Rome
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