4 ms·
As a human, out of curiosity I've previously tried to classify random tweets into emotions and failed, there just isn't enough context to make the judgements no
by msy 13y ago
As a human, out of curiosity I've previously tried to classify random tweets into emotions and failed, there just isn't enough context to make the judgements not arbitrary. In consequence I'm deeply suspicious of software that claims to be able to do so.
- Shank 13y agoI worked with a lot of Twitter data over the summer as part of an internship. I can say that signal to noise ratio is so abysmally inverted, this is almost certainly doing a lot of filtering just to get meaningful source data. For instance, you have to filter out most posts with links (because they tend to have very little associated data, or are spam), anything in languages you don't have parsers or datasets for, etc. Then you can cut on character count (because there are a surprising amount of useless tweets that are under 5-9 characters)... As others have and will continue to state, this further cuts down the sample size of an already fairly small sample (500+ million in the world[0]). If you want to be specific and only look at a single nation, you're cutting that sample size based on who has location turned on and/or broadcasts it in their profile. This is a significantly smaller number. Edit: This is obviously a better sample size than a random poll of individuals, however, but that doesn't mean that the cumulative quality will be drastically higher. [0] - http://www.statisticbrain.com/twitter-statistics/ http://www.statisticbrain.com/twitter-statistics/ (sources from three different input points)