Election Prediction Using Social Media through Sentiment Analysis

The project "Election Prediction through social media using Sentiment Analyis" is one of the hotest area of research in now a days. Already people have done a lot of work. In this area we are going to using deep learning techniques  to do prediction about election using people sentiments throug

Project Title

Election Prediction Using Social Media through Sentiment Analysis

Project Area of Specialization

Artificial Intelligence

Project Summary

The project "Election Prediction through social media using Sentiment Analyis" is one of the hotest area of research in now a days. Already people have done a lot of work. In this area we are going to using deep learning techniques  to do prediction about election using people sentiments through flickr and twitter data. Following are the steps which we have planned to execute in this project:

• First of all we have to collect the raw data in the form of tweets and images using API's.
• Then we will perform data preprocessing technique to produce useful insights.
• After preprocessing of data we will label our data through sentiments.
• Then we will apply deep learning algorithms to predict our results.

We will perform such type of steps that will the source of removing biasness from the data that will be helpful in correct labeling of data. Nowadays, there are multiple sources through which fake and biased sentiments can get easily. By using textual and visual sentiment analysis technique, it will minimize this problem to a greater extent. We are also working on to genrate large amount of data. Ultimately, it will produce our high accuracy.

Project Objectives

Following are the objectives of the project:

• To make the accurate election prediction
• To minimize the biasness of people sentiments to a maximum level
• To manage and control the campaigns required for election.
• As it is cost effective method, utimately it will reduce the cost required for election campaigns.

Project Implementation Method

The steps involved in our project implementation method are:

• In requirment analysis we have to find the problem that is correct prediction of elections.
• We have to collect data through social media and ultimately perform data preprocesing techniques
• We have to train our model through training the data.
• In validation phase we will perform the validation of model through testing of unseen data.
• Then our model will predict the correct prediction of election.

Benefits of the Project

Following are the benefit of the project:

• Make an accurate prediction.
• Minimize the biasness of people sentiments to a maximum level
• Managing and controling the campaigns required for election.
• As it is cost effective method, utimately it will reduce the cost required for election campaigns.

Technical Details of Final Deliverable

The technical detail of our final deliverable is following:

We will present a prediction model based on Deep learning Techniques. We will make use of LSTM which is recurring neural network. 

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

IT

Core Technology

Big Data

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com