Language sentiment analysis and neural networks... for trolls.

Troll is a tool for performing sentiment analysis (ie: "is this naughty or nice") on arbitrary blocks of text and associating it with a unique user. Using this data, combined with a rather naivé neural network and some training, users can be classified as "trolls".

Troll uses Redis for data storage. Once Redis is up and running, you can install Troll using NPM:

npm install troll
var troll   = require('troll');
troll.analyze('This is great!', 'user123', function (errresult) {
    console.log(result);    // 6 
troll.analyze('I hate this stupid thing.', 'user456', function (errresult) {
    console.log(result);    // -10  

Before attempting to classify a user, you'll need to train Troll. You can specify your own training data or use a basic set that is included. To load the included training set:

troll.train(function (errresult) {
    console.dir(result);    // { error: 0.005, iterations: 72 } 

Once trained, now you can classify:

troll.classify('user123', function (errresult) {
    console.dir(result);    // { total: 9, sum: 36, troll: 0.010294962292857838 } 

The value returned for the troll key represents the probability of that user being a troll. A value close to zero means that they are most likely not a troll, while a number closer to one means that they are.

Troll uses your environment by looking at process.env for connection settings. If none are found, default Redis connection settings are used:


npm test