Election Prediction using Twitter Data by means of vector modeling.

This is R project that is done to analyse data from twitter to prediction popularity of candidates
for elections.

What it does

• Extract Raw Data from Twitter and Store it into Mongo DB.
• Process the stored data and filter the data based on following parameter
  • Location of phenomenon
  • Search Terms related to election
  • Number of tweets
  • Time window of the phenomenon
  • User Profile characteristics
• Calculates the following parameters
  • Relative Frequency - Ratio of total tweets per day to no. of tweets of particular party.
  • Positive Negative Ratio - Ratio of positive no. of tweets to that of negative no. of tweets.

Steps to execute the project

• Download / Clone the repository
• Install Mongo DB
• Start Mongo Database in localhost
• Run command mongod.exe —dbpath ‘path_to_database_folder’
  Rscript main.R
• Plots will be generated in a PDF file.

Modules contained in the project

• function.R — function module containing the main functions to be used in the project
• environment.R — contains the global parameters to be used
• packages.R — contains the list of libraries / R packages to be used in the project
• main.R — main module where the project runs.
• mine.R — module that must be executed to mine data from twitter API as needed.

Database Configurations

• Start Mongo DB server and that’s it. You database is ready to be used.