http://github.com/Tawlk/synt

Synt (pronounced: "cent") is a python library aiming to be a general solution to identifying a given peice of text, particularly social network statuses, as either negative, neutral, or positive.

• Can create training data from random twitter statuses
• Uses emoticons to automatically sort out positive/negative training samples
• Includes a manual trainer to classify posts by hand
• Ability to granularly generate classifiers by adjusting sample/token/entropy levels

• A running Redis server
• pip
• virtualenv (recommended)
• python2.7
  • sqlite3 issue was fixed in 2.7 issue
  • argparse
• PyYAML==3.09
  • unfortnatley nltk requires pyyaml before it can be installed bug

1. Grab the latest synt:

```bash
pip install -e git+https://github.com/Tawlk/synt/#egg=synt
```

2. Grab the sample database to train on (or build one (below)):

```bash
synt collect fetch
```

If you'd prefer to build a fresh sample db and have the time, just run collect with
the desired number of recent posts you wish to fetch.

```bash
synt collect 1000
```

**Note**: This also can update an existing database. For instance, If you
decided to initially use fetch to populate the db, adding more via collect
should still work.

3. Build classifier

```bash
synt train
```

4. Usage:

```python
from synt import guess
guess('My mother in law makes me do bad things and I think pandas are icky!')
```
Or on the command line:

```bash
synt guess 'I want to chase poodles. That makes me happy and joyful :-D'
```

This will return a score from -1 .. 1 negative to positive respectivley.

Anything close to 0 should be considered neutral.

Use at your own risk. You may be eaten by a grue.

Questions/Comments? Please check us out on IRC via irc://udderweb.com/#uw