4 ms·

I'll be writing this up in more detail soon, but the sentiment is basically derived through the ANEW dataset. This dataset scores a few thousand English words w

I'll be writing this up in more detail soon, but the sentiment is basically derived through the ANEW dataset. This dataset scores a few thousand English words with sentiment values from 1 (very unhappy) to 9 (very happy). I find the sentiment value for each word in a tweet and then average that value by the amount of words in a tweet to get the sentiment value for each tweet.

JonnieCache 15y ago
This seems a rather simplistic approach when analysing sentiment in a country known the world over for truly impenetrable sarcasm, and the application of irony so blunt that it often boils down to simply stating the exact opposite to what you actually mean, often with a total absence of syntactic cues that this is happening. The humour that brits derive from this often seems like it is defined by fact that these cues aren't there at all. In short, I think you'd have to do a lot of quite complex higher order link analysis to determine people's true opinions. In this example, the royal wedding, imagine the following tweet: "This is a fantastic and important day for britain, a fabulous use of public money, I feel so proud to celebrate such a deserving couple!!" Put it like this, I wouldn't bet money on a simple word scoring algorithm getting the intended sentiment correct here.
- robhawkes 15y ago
  Thanks for your input Jonnie, you've highlighted one of the main limitations of text-based sentiment analysis. I've never always asserted that the sentiment derived from this study is not indicitive of "true" sentiment of an individual person. Rather, the sentiment derived here is simply saying that people on Twitter are using particular words that connotate happiness or sadness. This is the same limitation that most other studies have found, but it doesn't make the results any less interesting. Another way to look at it is as signal-to-noise. Whatever stereotypes of the UK exists, we don't all talk sarcastically (at least not all the time). Because of this the majority of tweets, which are probably not sarcastic, average out the hard to read tweets. Again, this is something that other studies have found as well. My aim here isn't to fault the method of sentiment analysis. I'll leave that to the guys at Florida University who created it. :)
  - JonnieCache 15y ago
    Oh I didn't mean to criticise anything you're doing. There's no such thing as bad data mining, only bad analysis of the results :) I just worry that people in our governments and security services will sieze on work like this which is largely being carried out for the amusement and satisfaction of academics and general geeks, and decide that it is appropriate to make specific judgements about specific people based on the data. It doesn't help that I read this article just after I woke up this morning: http://www.guardian.co.uk/uk/2011/may/03/protester-sue-police-secret-surveillance http://www.guardian.co.uk/uk/2011/may/03/protester-sue-polic... Combine it with this recent episode: (the guy was eventually convicted and fined) http://www.guardian.co.uk/world/2010/jan/18/robin-hood-airport-twitter-arrest http://www.guardian.co.uk/world/2010/jan/18/robin-hood-airpo... ...and with all the recent hype over 'cyberwar,' I start feeling a bit chilly.
    - robhawkes 15y ago
      I agree completely. These results shouldn't be simply taken at face value if they're to be used for further analysis.

JonnieCache 15y ago

This seems a rather simplistic approach when analysing sentiment in a country known the world over for truly impenetrable sarcasm, and the application of irony so blunt that it often boils down to simply stating the exact opposite to what you actually mean, often with a total absence of syntactic cues that this is happening. The humour that brits derive from this often seems like it is defined by fact that these cues aren't there at all. In short, I think you'd have to do a lot of quite complex higher order link analysis to determine people's true opinions. In this example, the royal wedding, imagine the following tweet: "This is a fantastic and important day for britain, a fabulous use of public money, I feel so proud to celebrate such a deserving couple!!" Put it like this, I wouldn't bet money on a simple word scoring algorithm getting the intended sentiment correct here.

robhawkes 15y ago
Thanks for your input Jonnie, you've highlighted one of the main limitations of text-based sentiment analysis. I've never always asserted that the sentiment derived from this study is not indicitive of "true" sentiment of an individual person. Rather, the sentiment derived here is simply saying that people on Twitter are using particular words that connotate happiness or sadness. This is the same limitation that most other studies have found, but it doesn't make the results any less interesting. Another way to look at it is as signal-to-noise. Whatever stereotypes of the UK exists, we don't all talk sarcastically (at least not all the time). Because of this the majority of tweets, which are probably not sarcastic, average out the hard to read tweets. Again, this is something that other studies have found as well. My aim here isn't to fault the method of sentiment analysis. I'll leave that to the guys at Florida University who created it. :)
- JonnieCache 15y ago
  Oh I didn't mean to criticise anything you're doing. There's no such thing as bad data mining, only bad analysis of the results :) I just worry that people in our governments and security services will sieze on work like this which is largely being carried out for the amusement and satisfaction of academics and general geeks, and decide that it is appropriate to make specific judgements about specific people based on the data. It doesn't help that I read this article just after I woke up this morning: http://www.guardian.co.uk/uk/2011/may/03/protester-sue-police-secret-surveillance http://www.guardian.co.uk/uk/2011/may/03/protester-sue-polic... Combine it with this recent episode: (the guy was eventually convicted and fined) http://www.guardian.co.uk/world/2010/jan/18/robin-hood-airport-twitter-arrest http://www.guardian.co.uk/world/2010/jan/18/robin-hood-airpo... ...and with all the recent hype over 'cyberwar,' I start feeling a bit chilly.
  - robhawkes 15y ago
    I agree completely. These results shouldn't be simply taken at face value if they're to be used for further analysis.