\It makes sense": Using an Autoassociative Neural Network to explore typicality in computer mediated discussions

ProjectH, a research group of a hundred researchers, produced a huge amount of data from computer mediated discussions. The data classi ed several thousand postings from over 30 newsgroups into 46 categories. One approach to extract typical examples from this database is presented in this paper. An Autoassociative Neural Network is trained on all 3000 coded messages and then used to construct typical messages under certain speci ed conditions. With this method the neural network can be used to create \typical" messages for several scenarios. This paper illustrates the architecture of the Neural Network that was used and explains the necessary modi cations to the coding scheme. In addition several \typicality sets" produced by the Neural Net are shown and their generation is explained. In conclusion the ANN is used to explore threads and the types of messages that typically initiate or contribute longer lasting threads.