Home

This repository contains several bits of R code to undertake text mining to look for emergent trends and "weak signals".

• Background info on "weak signals" is on my blog @ Weak Signals and Text Mining I - An Introduction to Weak Signals
• An outline of relevant text mining techniques and some ideas for using them to look for weak signals is given in a follow-on posting @ Weak Signals and Text Mining II - Text Mining Background and Application Ideas

The subject of the work is "technology enhanced learning" (aka "educational technology", "e-learning", ...) but the method is general.

Rising and Falling Terms

This is currently the only realisation of the ideas described in "Weak Signals and Text Mining II - Text Mining Background and Application Ideas". An elementary statistical test is complemented by the calculation of auxillary measures of novelty, subjectivity and author centrality. A separate page describes the Technical Details of the Rising and Falling Terms Method. An interpreted walk-through of results also comprises a form of qualitative evaluation of the method and indicates where care is needed in interpreting the results {to be written}.

Output and Results

Report created using "Rising and Falling Terms" on 2010 season conferences (ECTEL, ICALT, CAL, ICWL) @ http://arc12.github.com/Text-Mining-Weak-Signals-Output/Rising%20and%20Falling%20Terms/Union%20B/2010/Report.html

Output Index: http://arc12.github.com/Text-Mining-Weak-Signals-Output/index.html

Acknowledgements

This work was undertaken as part of the TEL-Map Project; TEL-Map is a support and coordination action within EC IST FP7 Technology Enhanced Learning.