Twitter Sentiment Analysis

1. 1
UNIVERSITY INSTITUTE OF COMPUTING
Master of Computer Applications
Minor Project-Rubric-1
Twitter Sentiment Analysis
Rubric-1 Presentation DISCOVER . LEARN . EMPOWER
Submitted by
NAME OF THE CANDIDATE(S):
SHRUTI GUPTA (21MCA2251)
UJJWAL SINGH (21MCA2202)
AMAN DEEP TIWARI (21MCA2170)
Supervisor Name: Harmanjeet Singh
Employee Code: E8042
Designation: Supervisor

2. Presentation Outline
2
• Introduction to Project
• Technology Used
• Recognition & knowledge of relevant contemporary issues
• Project Features
• Scope
• Objective

3. Introduction
3
Sentiment analysis is the task of finding the opinions and affinity of people towards
specific topics of interest. Be ita product or a movie, opinions of people matter, and it af-
fects the decision-making process of people. The first thinga person does when he or she
wants to buy a product on-line, is to see the kind of reviews and opinions that
peoplehave written. Social media such as Facebook, blogs, twitterhave become a place
where people post their opinions oncertain topics. The sentiment of the tweets of a
particularsubject has multiple usage, including stock market analysisof a company,
movie reviews, in psychology to analyze themood of people that has a variety of
applications, and so on.Sentiments of tweets can be categorized into many cat-egories
like positive, negative, neutral, extremely positive,extremely negative, and so on. The
two types of sentimentsconsidered in this classification experiment are positive
andnegative sentiments. The data, being labeled by humans,has a lot of noise, and its
hard to achieve good accuracy.

4. Technology Used
4
SOFTWARE REQUIREMENTS:-
Operating System: Windows 7/8/8.1/10
Python 3
Django
Html,Css,Javascript,Bootstrap
Machine Learning
NLP
HARDWARE SPECIFICATIONS:-
Processor : Intel i5 or more
Motherboard : Intel® Chipset Motherboard.
Ram : 8GB or more
Cache : 512 KB

5. Recognition & knowledge of relevant
contemporary issues
5
Sentiment Analysis is a very challenging task. Following are some of the challenges faced in
1. Identifying subjective parts of text:
Subjective parts represent sentiment-bearing content. The same word can be treated as
subjective in one case, or an objective in some other
2. Domain dependence:
The same sentence or phrase can have different meanings in different domains
3. Sarcasm Detection:
Sarcastic sentences express negative opinion about a target using positive words in unique way.
4. Internationalization
Current Research work focus mainly on English content, but Twitter has many varied users
from across.
5. Noisy text: text contains lot of repetition and duplication creates a big issue

6. Project Features
• Sorting Data at Scale
• Real-Time Analysis
• Consistent criteria
• accuracy
• speed and time
6

7. The objectives of the study are first, to study the sentiment analysis in
microblogging which in view to analyze feedback from a customer of an
organization’s product;
second, is to develop a program for customers’ review on a product which allows
an organization or individual to sentiment and analyzes a vast amount of tweets
into a useful format.
Twitter sentiment analysis allows you to keep track of what's being said about
your product or service on social media, and can help you detect angry customers
or negative mentions before they they escalate.
Objective

8. Scope
This project will be helpful to the companies, political parties as well as to the
common people.
It will be helpful to political party for reviewing about the program that they are
going to do
or the program that they have performed. Similarly companies also can get review
about their
new product on newly released hardware or softwares. Also the movie maker can
take review
on the currentlyrunning movie. Byanalyzing the tweets analyzer can get result on
how positive
or negative or neutral are peoples about it

9. THANK YOU