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Twitter Sentiment Analysis demonstration powered by MongoDB

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MongoDB Demonstration

This demonstration is used to show some of the key features of MongoDB

Installation

MongoDB Database Setup

You should use MongoDB 2.6.x or later. (use Full Text Search : http://docs.mongodb.org/manual/core/index-text/ )

Create indexes in the twitter database, from the mongo shell:

use twitter

db.messages.ensureIndex( {'text':'text'})

db.messages.ensureIndex( {'coordinates.coordinates':'2dsphere'})

db.messages.ensureIndex( {'id' : 1})

db.sentiments.ensureIndex( {'brand' : 1}, {dateTime : -1} )

Create a configuration document used by the injector and application. (Screen will come)

db.config.save({
"_id" : "keywords",
"keywords" : [
	{
		"value" : "apple",
		"label" : "Apple"
	},
	{
		"value" : "mongodb",
		"label" : "MongoDB"
	},
	{
		"value" : "amazon",
		"label" : "Amazon"
	},
	{
		"value" : "google",
		"label" : "Google"
	},
	{
		"value" : "ford",
		"label" : "Ford"
	}
]
})

TODO: more index to setup

Python Injector

See Python Project

Do not foret to configure your Twitter API Keys. (see importer.py file )

Node/AngularJS Application

See Node Project

To Do

The application is using direct find and aggregate, for scalability reason I am planning to change the implement and use a "prep-aggregated" approach see here

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