Day by day, social media micro-blogs becomes the best platform for the user to express their views and opinions in-front of the people about different types of product, services, people, etc. These social media micro-blogs like twitter becomes the biggest source of information and knowledge. Now days, lot of manufactures take a poll of public on micro-blogs about their new upcoming product to judge and to analyze their reactions for knowing the sense of their sentiments about those products. Now researchers focus on developing a technology which can identify and detect overall sentiments of users who are present on micro-blogs. Here, in this article, we focus on one of the famous social media micro-blog that is “Twitter”. We have explained different models to classify Tweets posted on the Twitter into positive, negative and neutral sentiments. Through this system, we try to do Sentiment Analysis of Twitter Data. We did the sentiment analysis of twitter data using two classifications models. The first one is three way task model for classifying positive, negative and neutral classes sentiments and second is , binary task based model that classify sentiments into two classes that is positive and negative.
Some companies or organization use sentimental analysis of twitter data to get public response and opinions about their product or services. Evenif there are few government bodies that are doing sentiment analysis of twitter data to analyze public responses about some social issues or some new government legislations or policies. Now days, politicians are also required good social indexing to get election ticket that, can be analyzed with the help of that political leader’s twitter data sentimental analysis. Tweet’s views, comments and likes are responsible for analysing the popularity of celebrities, political leader or businessman, etc. Sometimes lot of survey companies used to do sentimental analysis of various sensational issues on twitter data to figure out the impact of those sensational issues on public and media. This kind of analysis is also done by some big giant companies before manufacturing their products to know public interest in it. Sometimes, through this kind of sentiment based analytics surveys of twitter data, companies may get public positive and negative feedback with their hidden sentiment about their company and previous products and services which might be helpful for them to improve their next upcoming product and future services. Now as per new research, by doing sentimental analysis of any user’s twitter data, we can find out approximate behaviour or thought process of that user. In some competitive exams, some organization start adapting this test to know thought process and social behaviour of that candidate.
Static Pages and other sections :
These static pages will be available in project Sentiment Analysis of Twitter Data
- Home Page with good UI
- Home Page will contain an animated slider for images banner
- About us page will be available which will describe about the project
- Contact us page will be available in the project
Technology Used in the project Sentiment Analysis of Twitter Data
We have developed this project using the below technology
- HTML : Page layout has been designed in HTML
- CSS : CSS has been used for all the desigining part
- Python : All the business logic has been implemented in Python
- MySQL : MySQL database has been used as database for the project
- Django : Project has been developed over the Django Framework
- Python Library : We have used numpy, nltk, pyparsing, PySocks python library
Supported Operating System
We can configure this project on following operating system.
- Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install Python 3, PIP, Django.
- Linux : We can run this project also on all versions of Linux operating system
- Mac : We can also easily configured this project on Mac operating system.