# brain of mat kelcey

## sentiment analysis training data using mechanical turk

March 12, 2010

want to try doing some sentiment analysis work on tweets but i need some good training data.

i could label a heap of tweets myself as being positive, neutral or negative but instead this seems to be the perfect job for mechanical turk

so i put up 100 'cream cheese' tweets on mechanical turk, asked for 3 opinions per tweet and offered $0.01 per opinion. took under 30 minutes to get back all 300 opinions and only cost$4.50 ($3 for the work,$1.50 admin fee)

the results are interesting in themselves...

mostly they are consistent;

for example all three sentiments for bagels and cream cheese for breakfast. very original were neutral

and all three sentiments for very few things are as good as a warm nyc bagel with cream cheese first thing in the am were positive.

but occasionally they aren't consistent;

the tweet developing a recipe for orange cream cheese swirled cardamom brownies... that's too long a name. hmm... suggestions? had one positive, one neutral and one negative

interestingly there was no case of a tweet having all opinions being negative; even bad idea. dont eat bagel with mixed berry cream cheese, right after u washed ur mouth with listerine. . ended up with two negatives and one positive (?)

hmmmm