Spammer Detection and Fake User Identification in E-Commerce Site

Authors

  • Gayke P.S Department of Information Technology, DVVP COE Ahmednagar, Maharashtra, India
  • Kardile S Department of Information Technology, DVVP COE Ahmednagar, Maharashtra, India
  • Dongare N Department of Information Technology, DVVP COE Ahmednagar, Maharashtra, India
  • Pathare S Department of Information Technology, DVVP COE Ahmednagar, Maharashtra, India
  • Sakat P Department of Information Technology, DVVP COE Ahmednagar, Maharashtra, India

DOI:

https://doi.org/10.26438/ijcse/v9i7.2225

Keywords:

Sentiment Analysis,, Polarity, Natural Language Processing, Product reviews

Abstract

Sentiment analysis is a technique which is used for Natural language Processing, text analysis, text pre- processing etc. are the trending research field in current time. Sentiment analysis using different techniques and tools for analyze and arrange the unstructured data in a manner that objective results can be generated from them. By using these techniques, allow a computer to understand what is being said by humans. Sentiment analysis uses different techniques to determine the sentiment from a text or sentence or expression. The Internet is a huge source of natural language. People share their thoughts and experiences which are subjective in nature. Many a time, it is difficult for customer to identify whether the product shown by seller is good or bad. Companies may also unaware of customer requirements. Based on product reviews it is necessary to understand the perspective of customer towards a particular product. However, these are in huge amount; therefore a summary of positive and negative reviews needs to be generated. In this project, the main focus is on the review of products and techniques used for extract feature wise summary of the product and analyzed them to form an authentic review. Future work will include more product reviews websites and will focus on higher level natural language processing tasks. Using best and new techniques or tool for more accurate result in which the system except only those keywords which are in dataset rest of the words are eliminated by the system.

References

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Published

2021-07-31
CITATION
DOI: 10.26438/ijcse/v9i7.2225
Published: 2021-07-31

How to Cite

[1]
P. V, S. Kardile, N. Dongare, S. Pathare, and P. Sakat, “Spammer Detection and Fake User Identification in E-Commerce Site”, Int. J. Comp. Sci. Eng., vol. 9, no. 7, pp. 22–25, Jul. 2021.

Issue

Vol. 9 No. 7 (2021): IJCSE July Edition

Section

Research Article

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