Clustering on the Net
Applying an autoassociative neural network to computer-mediated discussions
Bibliographic Data
| ID | 12448977 |
|---|---|
| Authors | Michael R Berthold (0000-0001-9095-3283, The University of Sydney, corresponding author), Fay Sudweeks (0000-0003-0237-3671, The University of Sydney, corresponding author), Sidney Newton (0000-0001-8334-1916, Western Sydney University, corresponding author), Sid Newton, Rebecca Coyne (0000-0002-1918-7704, University of Edinburgh, corresponding author), Richard D Coyne |
| Year | 2006 |
| Volume | 2 |
| Issue | 4 |
| Pages | 0-0 |
| Publication date | 2006-06-23 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Computer-Mediated Communication (JOURNAL) |
| Journal identifiers | ISSN: 1083-6101 • E-ISSN: 1083-6101 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/j.1083-6101.1997.tb00202.x |
| OpenAlex | W2045386370 |
| Language | EN |
| Citations received | 2 |
| References cited | 7 |
ProjectH, a research group of a hundred researchers, produced a huge amount of data from computer mediated discussions. The data classified 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 specified 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 modifications to the coding scheme. In addition several “typicality sets” produced by the neural net are shown and their generation is explained. In conclusion, the autoassociative neural network is used to explore threads and the types of messages that typically initiate or contribute longer lasting threads
Artificial neural network · Cluster analysis · Coding (social sciences · Computer network · Construct (python library · Data mining · Machine learning · Time delay neural network · Cognitive Science and Education Research · Computer Science · Multi-Agent Systems and Negotiation · Speech and dialogue systems · Artificial Intelligence
| Citations per year | 0.1 |
|---|---|
| Citation span | 2006 - 2010 (5) |
| Highly cited | No |