ABSTRACT
- The rise of social media has given people all around the world to converse and debate with a very large audience, the sheer amount of exposure a tweet or a post received is unprecedented.
- Recent development in the field of web Service with Machine learning has led to its usage in several different verticals.
- This can be used to predict the overall sentiment of the masses in relation to a political party or an individual.
- This project proposed a web based machine learning models to predict the chances of the winning the election based on the user or supporter opinions on the social media platform.
EXISTING SYSTEM
- In the past various approaches have been taken in order to solve the problem.
- Random forest and decision tree algorithms are among the popular ones.
- However, they have their own limitations and often fail to capture essential complex features involved in election prediction.
- Election prediction task intuitively requires a model to identify and weigh the features, same reasoning is used in natural language classification task where LSTMs are widely popular.
PROPOSED SYSTEM
- The proposed system consists of a Web Application.
- The goal was to determine the optimum tuning of hypermeters in order to increase the accuracy of the predicting model.
- Advantages
- • More accurate result can be possible by applying the Deep Neural Network (DNN) Algorithm due to its said accuracy.
- • Better Time efficiently.
- • Overcome traditional flaws with latest technology and methods.
In this project we introduce a model which utilizes DNN in order to carry out the task of election prediction.
Software Requirements:
- Front End – Anaconda IDE
- Backend – SQL
- Language – Python 3.8
Hardware Requirements
- •Hard Disk: Greater than 500 GB
- •RAM: Greater than 4 GB
- •Processor: I3 and Above
Including Packages
=======================
- * Base Paper
- * Complete Source Code
- * Complete Documentation
- * Complete Presentation Slides
- * Flow Diagram
- * Database File
- * Screenshots
- * Execution Procedure
- * Readme File
- * Addons
- * Video Tutorials
- * Supporting Softwares
Specialization =======================
- * 24/7 Support * Ticketing System
- * Voice Conference
- * Video On Demand
- * Remote Connectivity
- * Code Customization
- * Document Customization
- * Live Chat Support
election result prediction using machine learning, Predicting election results using machine learning GitHub, Sentiment analysis to predict election results using Python, Election prediction dataset, Election-analysis project using Python, deep learning-based election results prediction using twitter activity, Election results Python, AI election prediction, Election data analysis using Python, Election result prediction using Twitter sentiment