3 ms·
Very interesting paper. (non-scribd version would be nice.) I'm surprised the corpus of words is so small and that there is no attempt to provide context. It
by willvarfar 14y ago
Very interesting paper. (non-scribd version would be nice.)
I'm surprised the corpus of words is so small and that there is no attempt to provide context. It just wasn't what I was expecting. I was expecting more of a markov chain kind of setup.
In Swedish, for example, there are lots of negative words that are trendy to use in a way that is extremely positive, rather like "wicked!" in English slang.
- robhawkes 14y agoNon-scribd version: https://www.dropbox.com/s/5r3nfol818s4qna/People%20love%20a%20good%20smooch%20on%20a%20balcony%20-%20Monitoring%20mood%20in%20the%20UK%20via%20Twitter%20%28Rob%20Hawkes%29.pdf https://www.dropbox.com/s/5r3nfol818s4qna/People%20love%20a%... Context is sacrificed with the ANEW approach, though that's not to say that accuracy and results are compromised. It just means that you need to look at the output in a different way, after understanding the limitations of the input. In ANEW (the data-set used), words that imply multiple meanings are likely to receive more neutral values (it's all coded by humans). The SentiWordNet data-set is probably a little more like what you're expecting: http://sentiwordnet.isti.cnr.it/ http://sentiwordnet.isti.cnr.it/