Abstract:
In today’s lifeline online marketing is on it’s verge and keep increasing as people
buy and sell products online. Digital marketing is an interesting and trending
business platform. Sellers often post fake reviews on their products or pay people to
post reviews and give higher rating, most consumer usually see and select products
according to that product’s rating and review which can be turn into dissatisfaction
of consumer as he bought that product on the basis of fake reviews. To detect such
reviews various methods are being used in past works. In this paper the method is
being used is Sentiment Analysis (SA). SA has become one of the most interesting
topics in text analysis, due to its promising commercial benefits. SA detects fake
positive and fake negative reviews based on emotions in the opinion. In this study,
we used machine learning algorithm Support Vector Machine (SVM) to detect those
fake negative and fake positive reviews.
Reviews can be positive or negative which helps consumers to select product. This
paper aims to classify movie reviews into groups of positive or negative polarity by
using machine learning algorithms. For the movies data-sets we performed some
data scrapping library like Beautiful- soup and Request to scrap movies data-sets
and collected data-sets from websites
