I'm looking for a dataset for moods or emotions (Happy, Angry, Sad) classification. That's to classify the sentiment of a given text. I would like to use Naive Bayes classifier for this analysis. Not only to train and test the model with the dataset, but rather to practice doing sentiment classification. Do you suggest any resources?
Some nice data sets for practicing sentiment classification are:
- Sentiment 140
- Dataset by Sanders
- Another source
- This one on Github
- One from a Kaggle contest
- EMOTIONAL SENSOR DATA SET 1.0.8
These are some open datasets which contain emotions like happy, sad, etc:
- Affective Sciences (Data in .sav data files)
This would be a good data source and the researcher also done a work on it. refer it too.
Why not you use Twitter Search API to search your particular type text, then do some text modification. Sorry, I am not expert, it is just an idea.
The best one I know is this:
this is also available in MySQL format!
It's the email corpus of Enron during the moments when it collapsed. The emails are clearly characterized by underlying feelings.
This dataset is quite unique and heavily described in the podcast Linear Digressions. It's one of a kind because after privacy laws kicked in it is not possible to ever get anything else like it again.