<commit_before># Synt #
  
  <http://github.com/lrvick/synt>

## About ##

  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.

## Current Features ##
 
  * 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

## Usage / Installation ##

  1. Collect a large amount of samples using the automated trainer
    
        python auto-trainer.py

    As a rule of thumb anything less than 200,000 leads to less that useful results.

    Optionally you can use the rather large ( 2mil tweets / 100M ) pre-collected database <commit_msg>update readme repo link<commit_after># Synt #
  
  <http://github.com/Tawlk/synt>

## About ##

  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.

## Current Features ##
 
  * 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

## Usage / Installation ##

  1. Collect a large amount of samples using the automated trainer
    
        python auto-trainer.py

    As a rule of thumb anything less than 200,000 leads to less that useful results.

    Optionally you can use the rather large ( 2mil tweets / 100M ) pre-collected database 
{'fraction_non_alphanumeric': 0.05704882062534284, 'fraction_numerical': 0.012068019747668678, 'mean_word_length': 3.606060606060606, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1576631', 'n_tokens_mistral': 509, 'n_tokens_neox': 461, 'n_words': 229}