Version 1.31 [October 7, 2013]
This new version has a new "agreement" option called "subtract". This option will add congruence ties to the network and subtract conflict ties from the network. The result is a signed, weighted graph with positive edge values indicating belief similarity and negative values indicating a tendency for belief conflict. In visone, for example, the attribute manager lets you select and remove all negative ties of the resulting network and retain only those connections where belief congruence exceeds belief conflict between two actors. In rDNA, "agreement = 'subtract'" will yield such a signed network.
A major update has been in progress for a while. An experimental version of this major update will be released in a couple of months. In the meantime, version 1.31 should be used.
You should have a Java Runtime Engine 1.6 or higher installed on your system. DNA will not work with a Java version lower than 1.6!
DNA has been tested on various Windows, Linux and MacOS versions.
Some Java installations offer to start the software via double-clicking the file or right-clicking and selecting an entry from the context menu. However, the preferred way of starting DNA is from the command line by executing the command java -jar dna-1.31.jar from the folder where you have saved the file. Please consult the documentation for more details.
Previous versions of DNA are available upon request. A version history is included in the manual.
If you have trouble installing or using the software, please post a message to the DNA-help mailing list. Please also report bugs. Thank you!
Copyright and terms
Please note that Philip Leifeld, University of Konstanz, owns the copyright of the software Discourse Network Analyzer (DNA), the network export algorithms, the underlying discourse network model, and the documentation. You may, however, use them free of charge (citing some of the relevant work would be nice). Manipulation or redistribution of the code are prohibited. The author does not assume liability in case of data loss.