Subject_Sentiment_analysis

-Arihant Jain

Why Sentiment Analysis ?

Millions of messages are appearing daily in popular web-sites that provide services for microblogging such as Twitter, Tumblr, Facebook. Authors of those messages write about their life, share opinions on variety of topics and discuss current issues. Because of a free format of messages and an easy accessibility
of microblogging platforms, Internet users tend to shift from traditional communication tools (such as traditional blogs or mails) to microblogging services. As more and more users post about products and services they use, or express their political and religious views, microblogging web-sites become valuable sources of people’s opinions and sentiments. Such data can be efficiently used
for marketing or social studies.

“This is sample project to analyze sentiments based on particular subject”
We would like to add Facebook Sentiment Analysis based on text and also emotiocon as of now only twitter sentiment analysis available.
“”””You can also commit to Facebook_Sentiment_Analysis.py using facebook Graph API.”””””
In our coming project, we will attach all our code and develop android project. So that we can graphically interact with it.

“How to Run ?””

You can clone and run subject_sentiment_Analysis.py in python using python Subject_sentiment_Analysis.py

You need to install first these python libraries
pip install tweepy
pip install TextBlob
pip install sckit-learn

Use of code is lincensed under MIT Lincense

Applications of Sentiment Analysis
Sentiment Analysis finds its application in a variety of domains.
A. Online Commerce

The most general use of sentiment analysis is in ecommerce
activities. Websites allows their users to
submit their experience about shopping and product
qualities. They provide summary for the product and
different features of the product by assigning ratings or
scores. Customers can easily view opinions and
recommendation information on whole product as well
as specific product features. Graphical summary of the
overall product and its features is presented to users.
Popular merchant websites like amazon.com provides
review from editors and also from customers with
rating information. http://tripadvisor.in is a popular
website that provides reviews on hotels, travel
destinations. They contain 75 millions opinions and
reviews worldwide. Sentiment analysis helps such
websites by converting dissatisfied customers into
promoters by analyzing this huge volume of opinions.

B. Voice of the Market (VOM)

Voice of the Market is about determining what
customers are feeling about products or services of
competitors. Accurate and timely information from the
Voice of the Market helps in gaining competitive
advantage and new product development. Detection of
such information as early as possible helps in direct and
target key marketing campaigns. Sentiment Analysis
helps corporate to get customer opinion in real-time.
This real-time information helps them to design new
marketing strategies, improve product features and can
predict chances of product failure.
Zhang et al.proposed weakness finder system
which can help manufacturers find their product
weakness from Chinese reviews by using aspects based
sentiment analysis. There are some commercial and
free sentiment analysis services are available, Radiant6,
Sysomos, Viralheat, Lexalytics, etc. are commercial
services. Some free tools like www.tweettfeel.com,
www.socialmention.com are also available.

C. Voice of the Customer (VOC)

Voice of the Customer is concern about what
individual customer is saying about products or
services. It means analyzing the reviews and feedback
of the customers. VOC is a key element of Customer
Experience Management. VOC helps in identifying
new opportunities for product inventions. Extracting
customer opinions also helps identify functional
requirements of the products and some non-functional
requirements like performance and cost.

D. Brand Reputation Management

Brand Reputation Management is concern about
managing your reputation in market. Opinions from
customers or any other parties can damage or enhance
your reputation. Brand Reputation Management (BRM)
is a product and company focused rather than customer.
Now, one-to-many conversations are taking place
online at a high rate. That creates opportunities for
organizations to manage and strengthen brand
reputation. Now Brand perception is determined not
only by advertising, public relations and corporate
messaging. Brands are now a sum of the conversations
about them. Sentiment analysis helps in determining
how company’s brand, product or service is being
perceived by community online.

E. Government

Sentiment analysis helps government in assessing
their strength and weaknesses by analyzing opinions
from public. For example, “If this is the state, how do
you expect truth to come out? The MP who is
investigating 2g scam himself is deeply corrupt.”.
this example clearly shows negative sentiment about
government.
Whether it is tracking citizens’ opinions on a new
108 system, identifying strengths and weaknesses in a
recruitment campaign in government job, assessing
success of electronic submission of tax returns, or
many other areas, we can see the potential for
sentiment analysis.”# subject_sentiment_analysis”