Detection of fake opinions on online products using decision tree and information gain
- Title
- Detection of fake opinions on online products using decision tree and information gain
- Creator
- Sanjay K.S.; Danti A.
- Description
- Online reviews are one of the major factors for the customers to purchase any product or to get service from many sources of information that can be used to determine the public opinion on the products. Fake reviews will be published intentionally to drive the web traffic towards the particular products. These fake reviewers mislead the customers to distract the purchasers mind. Reviewers behaviors are extracted based the semantical analysis of his review content for the purpose of identifying the review as fake or not. In this work the reviews are extracted from the web for a particular product, along with the reviews of several other information related to the reviewers also been extracted to identify the fake reviewers using decision tree classifier and Information Gain.Significance of the features on the decision is validated using information gain. Experiments are conducted on exhaustive set of reviews extracted from the web and demonstrated the efficacy of the proposed approach. 2019 IEEE
- Source
- Proceedings of the 3rd International Conference on Computing Methodologies and Communication, ICCMC 2019, pp. 372-375.
- Date
- 2019-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Decision Tree; Entropy; Fake; Information Gain; Opinion; Reply; Response; Reviews; Stars
- Coverage
- Sanjay K.S., Dept of Computer Applications, Bangalore Social and Educational Institute Management Studies, Bangalore, Karnataka, India; Danti A., Faculty of Engineering-CSE, Christ(Deemed to be University), Bangalore, Karnataka, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-153867808-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sanjay K.S.; Danti A., “Detection of fake opinions on online products using decision tree and information gain,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20810.