Product Reviews Classifications-A Data Science Approach

Reviewing the product is an important step for e-commerce platforms. Getting reviews from customers and analysis of reviews consumes many resources. As the number of reviews received day by day is increasing very rapidly, reviews should be classified as fake review and Genuine reviews. The total accumulation of reviews and analysis is different from natural language processing problem. Spammers are hired for biased reviewing of products. In this paper we put a novel comparison between purchase list and reviews. We have applied a method for finding duplicate reviews; measure the total numbers of reviews and their mismatch in counts, at the end count dispersion for every product and classification of reviews. We applied data science approach for classification and visualization to get fake reviews. We label the reviews either positive or negative based on comparison between them. A data science approach is applied because for a well-known product the reviews can goes up to many thousands.

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Email phishing: text classification using natural language processing

Computer Science and Information Technologies ◽

10.11591/csit.v1i1.p1-12 ◽

2020 ◽

Vol 1 (1) ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Priyanka Verma ◽

Anjali Goyal ◽

Yogita Gigras

Keyword(s):

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

Private Information ◽

Credit Card ◽

Solution Approach ◽

Main Motive ◽

Work Done ◽

Day By Day

Phishing is networked theft in which the main motive of phishers is to steal any person’s private information, its financial details like account number, credit card details, login information, payment mode information by creating and developing a fake page or a fake web site, which look completely authentic and genuine. Nowadays email phishing has become a big threat to all, and is increasing day by day. Moreover detection of phishing emails have been considered an important research issue as phishing emails have been increasing day by day. Various techniques have been introduced and applied to deal with such a big issue. The major objective of this research paper is giving a detailed description on the classification of phishing emails using the natural language processing concepts. NLP (natural language processing) concepts have been applied for the classification of emails, along with that accuracy rate of various classifiers have been calculated. The paper is presented in four sections. An introduction about phishing its types, its history, statistics, life cycle, motivation for phishers and working of email phishing have been discussed in the first section. The second section covers various technologies of phishing- email phishing and also description of evaluation metrics. An overview of the various proposed solutions and work done by researchers in this field in form of literature review has been presented in the third section. The solution approach and the obtained results have been defined in the fourth section giving a detailed description about NLP concepts and working procedure.

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