Feature Based Fuzzy Framework for Sentimental Analysis of Web Data

Title

Feature Based Fuzzy Framework for Sentimental Analysis of Web Data

Creator

Ahamed S.; Danti A.; Raghavendra S.P.

Description

Social mass media has emerged as a projectile platform for the evolution of web data. The sentimental Analysis where the huge textual online reviews are analyzed to extract the actual sentiment or emotions hidden in the reviews. In this paper an effective approach for sentimental analysis of web data is proposed which deploys the fuzzy based machine learning algorithm to accomplish fine-level sentiment analysis of huge online opinions by assimilating the fuzzy linguistic hedges influence on opinion descriptors. The seven layered categories are designed that uses SentiWordNet which has three stages: Pre-processing phase, Feature Selection Phase and Fuzzy based Sentiment Analysis phase. Various machine learning algorithms like AdaBoost, (IBK) K-Nearest Neighbour, (NB) Nae Bayes and (SVM)/SMO Support Vector Machine are used for classification. Jsoup is implemented for gathering web opinions which are subjected to initial processing task later applied with stemming and tagging. This fuzzy based methodology is investigated for Mobile, Laptops dataset, also compared with state-of-the-art approaches which demonstrate upper indication of 94.37% accurateness through Kappa indicators showcasing lesser error rates. The investigational outcomes are tested on training data using Ten-Fold cross validation which concludes that this approach can be efficaciously used in Sentimental analysis as an aid for online decision. 2019 IEEE.

Source

2019 International Conference on Data Science and Communication, IconDSC 2019

Date

2019-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Feature Based; Fuzzy Framework; Opinion mining; POS tagging; Score Count; Sentimental Analysis

Coverage

Ahamed S., Department of Computer Science, Government First Grade College, Soraba(T), Shimoga(D), Karnataka, India; Danti A., Dept. of Computer Science and Engg, Christ, Deemed to be University, Bangalore, Karnataka, India; Raghavendra S.P., Dept. of Computer Applications, J N N College of Engineering, Shimoga, Karnataka, India

Rights

Restricted Access

Relation

ISBN: 978-153869319-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IconDSC.2019.8816997

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072762917&doi=10.1109%2fIconDSC.2019.8816997&partnerID=40&md5=4d2e323a9f6da2d68cdc67b5a0f96d07