A REVIEW ON: SENTIMENT ANALYSIS FOR DRUG USING USER REVIEWS

Authors

  • SUPRIYA PHATAK Annasaheb DangeCollege of Engineering, Sangli, India
  • S.V. PATIL Annasaheb DangeCollege of Engineering, Sangli, India
  • RUPALI PATIL Annasaheb DangeCollege of Engineering, Sangli, India
  • NITINKUMAR ANEKAR MITCollege of Engineering, Pune, India

Keywords:

Aspect Detection,, Sentiment Analysis,, Topic Modeling

Abstract

Merchants selling products on the Web often ask their customers to review the products that they have purchased and the associated services. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. It also makes it difficult for the manufacturer of the product to keep track and to manage customer opinions. For the manufacturer, there are additional difficulties because many merchant sites may sell the same product and the manufacturer normally produces many kinds of products. In this research, we aim to mine and to summarize all the customer reviews of a product.

Downloads

Published

2021-03-27

Issue

2016: ICITER

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format
  2. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. NonCommercial — You may not use the material for commercial purposes .
  3. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
  4. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

 

Rights of Authors

Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.

How to Cite

SUPRIYA PHATAK, S.V. PATIL, RUPALI PATIL, & NITINKUMAR ANEKAR. (2021). A REVIEW ON: SENTIMENT ANALYSIS FOR DRUG USING USER REVIEWS. International Journal of Innovations in Engineering Research and Technology, 1-4. https://repo.ijiert.org/index.php/ijiert/article/view/1273