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This is a collection of mostly R code to use text mining to analyse conference abstracts, blogs and other sources in an attempt to look for "weak signals" (early signs of new trends), See the wiki pages for background etc.

branch: master
README.txt
This github project is for text mining for weak signals, initially in the scope of the TELMap project.

The initial "naive" approach is the "Rising and Falling Terms" method. The first versions of this simply looked for high percentage rise or fall in term frequency (or new terms) and did not attempt any formal statistical hypothesis testing. This version is hived off to the no-binomial branch, which is effectively dead.

The wiki will be used to link out to background material, stuff about TELMap etc.

Everything you find here is provided under an MIT Licence:
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# Copyright (c) Adam Cooper
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# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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