[Gundla, 4(12): December, 2015] ISSN: 2277-9655
(I2OR), Publication Impact Factor: 3.785
http: // www.ijesrt.com© International Journal of Engineering Sciences & Research Technology
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IJESRT
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH
TECHNOLOGY
SENTIMENT ANALYSIS AND VISUALIZATION OF CUSTOMER REVIEWS
Ms.Apurva Vyankatesh Gundla
*
, Prof. Manisha S. Otari
*
Department of Computer Engineering, N.K.Orchid College of Engineering, Maharashtra, India
ABSTRACT
The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites
containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. All these
reviews are the opinions of people all over the world about different products. With the growing availability and
popularity of opinion-rich resources such as review forums for the product sold online, choosing the right product
from a large number of products have become difficult for the user. These sources are underutilized both by
consumers and businesses due to their unstructured nature, serial presentation, limited search tools, and low ratio of
useful information to the overall amount of data. The proposed system illustrates visual analysis system that
performs sentiment analysis and derives insight from a collection of online reviews of products from customer.
Effective visual analysis of online customer opinions is needed, as it has a significant impact on building a
successful business and helps the customers in decision making process. This paper presents background Study of
Sentiment Analysis or Opinion Mining and gives overview of proposed methodology with insights into past research
work.
KEYWORDS: Opinion Mining, Sentiment Analysis, Customer Reviews, Opinions.
INTRODUCTION
Sentiment Analysis refers to the use of natural language processing, text analysis and computational linguistics to
identify and extract subjective information in source materials. Sentiment analysis aims to determine the attitude of a
speaker or a consumer with respect to some topic or product. [1]Sentiment analysis, also called opinion mining, is
the field of study that analyzes people’s opinions, sentiments, evaluations, appraisals, attitudes, and emotions
towards entities such as products, services, organizations, individuals, issues, events, topics, and their attributes. [2]
It involves techniques from different disciplines like information retrieval, Natural Language Processing and Data
Mining. Sentiment Analysis is about extracting the opinions or sentiments when given a piece of text. “What other
people think” has always been an important piece of information for most of us during the decision-making process.
[3]Opinions or sentiments are central to almost all human activities and are key influencers of our behaviors. Our
beliefs and perceptions of reality, and the choices we make, are, to a considerable degree, conditioned upon how
others see and evaluate the world. Whenever we need to make a decision, we want to know others’ opinions. [2]
An Opinion is a judgment or belief a majority of people formed about a specific thing, not necessarily based on
fact/knowledge. Opinion generally refers to what a person thinks about something or opinion is a subjective belief,
and the result of emotion or facts interpretation. [4]
In the real world, businesses and organizations always want to find consumer or public opinions about their products
and services. Individual consumers also want to know the opinions of existing users of a product before purchasing
it, and others’ opinions about political candidates before making a voting decision in a political election. In the past,
when an individual needed opinions, he/she asked friends and family. When an organization or a business needed
public or consumer opinions, it conducted surveys, opinion polls, and focus groups. Acquiring public and consumer
opinions has long been a huge business itself for marketing, public relations, and political campaign companies.This
unique feature plays a vital role in determining on matters that have financial, medical, social or other implications.
Seeking second or third or many more opinions have fuelled the interest of researchers in the field of sentiment
mining. [5]
Many reviews are long, which makes it hard for a potential customer to read them to make an informed decision on
whether to purchase the product. If he/she only reads a few reviews, he/she only gets a biased view. The large
number of reviews also makes it hard for product manufacturers or businesses to keep track of customer opinions
and sentiments on their products and services. [6] The substantial gathering of opinions on the Web makes it
extremely tough to get helpful data effectively. Perusing all reviews and emotions to settle on an educated choice is
a much time taking task. Perusing distinctive and potentially even conflicting opinions composed by diverse