I think that's a brilliant idea. The point I'd like to make is that a
combination of data from different channels, would work the best. While for
instance, Twitter could be considered as the massive public view on some
product, Wikipedia data would be seen as an input about more professional
individuals with more accurate information. I think this is the place to
point to a recent paper by Osborne et al: Bieber no more: *First Story
Detection* using *Twitter* and
*Wikipedia*<http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CDQQFjAA&url=http%3A%2F%2Fresearch.microsoft.com%2Fen-us%2Fpeople%2Fmilads%2Fosbornetaia2012.pdf&ei=k4GbUKeJH5HPsgaM0YHQCw&usg=AFQjCNHdxw5DgY9-9OMRVx6l5znyknbhgQ>,
where they have used such combination to detect "First Stories".
On Thu, Nov 8, 2012 at 10:06 AM, Finn Årup Nielsen <fn(a)imm.dtu.dk> wrote:
Kerry Raymond: "A really exciting result would be the ability to predict
stock price movements from WP editing behaviour!"
I am actually funded by a project where we are trying that. We have looked
a bit on Twitter sentiment (like everyone else is doing), but now also do
Wikipedia sentiment analysis for companies.
You see an example here for the Lundbeck pharmaceutical company:
http://rb.imm.dtu.dk/base/c/**Lundbeck<http://rb.imm.dtu.dk/base/c/Lundb…
The plots are for Wikipedia sentiment through time, Twitter sentiment
through time and stock price (plots not aligned temporally).
Lundbeck had bad publicity last year. One of their drugs was, without
their acceptance, used for executions in United States. There is a drop in
Twitter sentiment in regard to that issue -- and also a slight drop in
Wikipedia sentiment. It is unclear to me whether the stock price movement
is related to that media issue.
I have not completed the analysis. But you see some further companies here
http://rb.imm.dtu.dk/base/c/ Mostly it is only the Swedish and Danish
companies I have run through the sentiment analysis.
Finn Årup Nielsen
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