The idea is to build a little web app that will scan the common news sources nightly, and compile a score for different words on how negative or positive the topic is described. For example, regarding the economy, the system should pick up speeches from the Fed, congress discussions, etc... The idea behind all this is from the Black Swan Book. The theory goes that the night before Thanksgiving, the turkey should have the highest confidence in the goodness of humans.
To achieve this, I will need an NLP mood analyzer, or in other words, Sentiment Analysis. Some open source tools to accomplish this are:
NPL Libraries:
- http://www.opencalais.com/ (Reuters Web Service)
- RapidMiner
- JavaNPL
- LingPipe
- Jane16
- http://garraf.epsevg.upc.es/freeling
Knowledge Understanding
- http://commons.media.mit.edu/en/
- http://www.opencyc.org/
- http://wordnet.princeton.edu/
- http://framenet.icsi.berkeley.edu/
News Sources
- http://cookbook.daylife.com/
- http://thomas.loc.gov/home/c110query.html (Government Enrolled Bills)
Ekman's research on universal facial expressions
[happy, sad, anger, fear, disgust, surprise]
Frustration – Repetition of low-magnitude anger
Relief – Fear followed by happy
Horror – Sudden high-magnitude fear
Contentment – Persistent low-level happy
2 comments:
RapidMiner can perform sentiment analysis or mood analysis or opinion mining or however you would like to call it. In addition to RapidMiner itself, you also need the RapidMiner Text Plugin for text mining and web mining. Both can be downloaded for free at
www.rapid-i.com
RapidMiner comes with an integrated web crawler, all required text pre-processing modules needed to process the collected web pages, and everything else to learn sentiment models and to deploy them.
Have fun,
Frank
I am working on a similar project (mood analysis of news sources). Thus far i have had fair success with conceptnet2.0 which has a `guess_mood()' function. My scripts have been running for a year on about 10 sources. conceptnet3.0 seems to be maturing though doesn't seem to have that particular method sadly.
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